Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Grid Connected Electricity Storage Systems (2/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IMPROVED SWARM INTELLIGENCE APPROACH TO MULTI OBJECTIVE ED PROBLEMSSuganthi Thangaraj
Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Metaheuristic optimization techniques especially Improved Particle Swarm Optimization (IPSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of IPSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper. This paper illustrates successful implementation of the Improved Particle Swarm Optimization (IPSO) to Economic Load Dispatch Problem (ELD). Power output of each generating unit and optimum fuel cost obtained using IPSO algorithm has been compared with conventional techniques. The results obtained shows that IPSO algorithm converges to optimal fuel cost with reduced computational time when compared to PSO and GA for the three, six and IEEE 30 bus system.
A Hybrid Control Scheme for Fault Ride-Through Capability using Line-Side Con...Suganthi Thangaraj
As the wind power installations are increasing in number, Wind Turbine Generators (WTG) are required to have Fault Ride-Through (FRT) capabilities. Lately developed grid operating codes demand the WTGs to stay connected during fault conditions, supporting the grid to recover faster back to its normal state. In this paper, the generator side converter incorporates the maximum power point tracking algorithm to extract maximum energy from wind turbine system. A hybrid control scheme for energy storage systems (ESS) and braking choppers for fault ride-through capability and a suppression of the output power fluctuation is proposed for permanent-magnet synchronous generator (PMSG) wind turbine systems. During grid faults, the dc-link voltage is controlled by the ESS instead of the line-side converter (LSC), whereas the LSC is exploited as a STATCOM to inject reactive current into the grid for assisting in the grid voltage recovery. A simple model of the proposed system is developed and simulated in MATLAB environment. The effectiveness of the system is validated through extensive simulation results
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
Optimal Unit Commitment Based on Economic Dispatch Using Improved Particle Sw...paperpublications3
Abstract: In this paper, an algorithm to solve the optimal unit commitment problem under deregulated environment has been proposed using Particle Swarm Optimization (PSO) intelligent technique accounting economic dispatch constraints. In the present electric power market, where renewable energy power plants have been included in the system, there is a lot of unpredictability in the demand and generation. This paper presents an improved particle swarm optimization algorithm (IPSO) for power system unit commitment with the consideration of various constraints. IPSO is an extension of the standard particle swarm optimization algorithm (PSO) which uses more particles information to control the mutation operation, and is similar to the social society in that a group of leaders could make better decisions. The program was developed in MATLAB and the proposed method implemented on IEEE 14 bus test system.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Grid Connected Electricity Storage Systems (2/2)Leonardo ENERGY
Development and use of Renewable Energy Sources is one of the key elements in European Electricity Research. However, connecting energy sources such as photovoltaics and wind turbines to the electricity grid causes significant effects on these networks. Bottlenecks are stability, security, peaks in supply & demand and overall management of the grid. Energy storage systems provide means to overcome technical and economic hurdles for large-scale introduction of distributed sustainable energy sources. The GROW-DERS project (Grid Reliability and Operability with Distributed Generation using Flexible Storage) investigates the implementation of (transportable) distributed storage systems in the networks. The project is funded by the European Commission (FP6) and the consortium partners are KEMA, Liander, Iberdrola, MVV, EAC, SAFT, EXENDIS, CEA-INES and IPE.
In this project 3 storage systems (2 Li-ion battery systems and a flywheel) have been demonstrated at different test locations in Europe. Additionally, a dedicated software tool, PLATOS (PLAnning Tool for Optimizing Storage), has been developed by KEMA to optimize the energy management of electricity networks using storage. For each network, the location, size and type of storage systems is evaluated for all possible configurations and the most attractive option is selected.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IMPROVED SWARM INTELLIGENCE APPROACH TO MULTI OBJECTIVE ED PROBLEMSSuganthi Thangaraj
Electrical power industry restructuring has created highly vibrant and competitive market that altered many aspects of the power industry. In this changed scenario, scarcity of energy resources, increasing power generation cost, environment concern, ever growing demand for electrical energy necessitate optimal economic dispatch. Practical economic dispatch (ED) problems have nonlinear, non-convex type objective function with intense equality and inequality constraints. The conventional optimization methods are not able to solve such problems as due to local optimum solution convergence. Metaheuristic optimization techniques especially Improved Particle Swarm Optimization (IPSO) has gained an incredible recognition as the solution algorithm for such type of ED problems in last decade. The application of IPSO in ED problem, which is considered as one of the most complex optimization problem has been summarized in present paper. This paper illustrates successful implementation of the Improved Particle Swarm Optimization (IPSO) to Economic Load Dispatch Problem (ELD). Power output of each generating unit and optimum fuel cost obtained using IPSO algorithm has been compared with conventional techniques. The results obtained shows that IPSO algorithm converges to optimal fuel cost with reduced computational time when compared to PSO and GA for the three, six and IEEE 30 bus system.
A Hybrid Control Scheme for Fault Ride-Through Capability using Line-Side Con...Suganthi Thangaraj
As the wind power installations are increasing in number, Wind Turbine Generators (WTG) are required to have Fault Ride-Through (FRT) capabilities. Lately developed grid operating codes demand the WTGs to stay connected during fault conditions, supporting the grid to recover faster back to its normal state. In this paper, the generator side converter incorporates the maximum power point tracking algorithm to extract maximum energy from wind turbine system. A hybrid control scheme for energy storage systems (ESS) and braking choppers for fault ride-through capability and a suppression of the output power fluctuation is proposed for permanent-magnet synchronous generator (PMSG) wind turbine systems. During grid faults, the dc-link voltage is controlled by the ESS instead of the line-side converter (LSC), whereas the LSC is exploited as a STATCOM to inject reactive current into the grid for assisting in the grid voltage recovery. A simple model of the proposed system is developed and simulated in MATLAB environment. The effectiveness of the system is validated through extensive simulation results
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
Optimal Unit Commitment Based on Economic Dispatch Using Improved Particle Sw...paperpublications3
Abstract: In this paper, an algorithm to solve the optimal unit commitment problem under deregulated environment has been proposed using Particle Swarm Optimization (PSO) intelligent technique accounting economic dispatch constraints. In the present electric power market, where renewable energy power plants have been included in the system, there is a lot of unpredictability in the demand and generation. This paper presents an improved particle swarm optimization algorithm (IPSO) for power system unit commitment with the consideration of various constraints. IPSO is an extension of the standard particle swarm optimization algorithm (PSO) which uses more particles information to control the mutation operation, and is similar to the social society in that a group of leaders could make better decisions. The program was developed in MATLAB and the proposed method implemented on IEEE 14 bus test system.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
Design methodology of smart photovoltaic plant IJECEIAES
In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
Economic Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Power system operation considering detailed modelling of the natural gas supp...IJECEIAES
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
This paper focuses on the artificial bee colony (ABC) algorithm, which is a nonlinear optimization problem. is proposed to find the optimal power flow (OPF). To solve this problem, we will apply the ABC algorithm to a power system incorporating wind power. The proposed approach is applied on a standard IEEE-30 system with wind farms located on different buses and with different penetration levels to show the impact of wind farms on the system in order to obtain the optimal settings of control variables of the OPF problem. Based on technical results obtained, the ABC algorithm is shown to achieve a lower cost and losses than the other methods applied, while incorporating wind power into the system, high performance would be gained.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
In this paper a load flow based method using MATLAB Software is used to determine the optimum location and optimum size of DG in a 43-bus distribution system for voltage profile improvement and loss reduction. This paper proposes analytical expressions for finding optimal size of three types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. Single DG installation case was studied and compared to a case without DG, and 43-bus distribution system is used to demonstrate the effectiveness of the proposed method. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of injecting real power only, DG capable of injecting reactive power only and DG capable of injecting both real and reactive power can also be identified with their optimal size and location using the proposed method. This paper has been analysed with varying DG size and complexity and validated using analytical method for Summer case and Winter case in 43-bus distribution system in Myanmar.
Keywords- analytical method,distributed generation,power loss reduction,voltage profile improvement.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Harvesting in electric vehicles: Combining multiple power tracking and fuel-c...IJECEIAES
Exploitation of green energy sources is essential to diminish the deterioration of our environment. The energy harvesting, represents an alternative to achieve greater range in electric and hybrid vehicles. An energy management strategy (EMS) must be optimized to obtain the best benefits in such vehicles, which is not a trivial task. If harvesting or energy recovery devices are added, the EMS becomes a dual-purpose algorithm: minimizing fuel consumption and maximizing energy harvest through maximum power point tracking (MPPT) controllers. Known studies consider separate EMS, one for traction and another for regenerative braking, without considering harvest devices such as solar panels, regenerative suspension, thermal generators, among others. Furthermore, the electronic power converters used, are not designed to handle such unequal power levels. In this article, an electronic platform to include multiple energy harvesting devices in a fuel-cell hybrid electric vehicle, was presented together with a multiple MPPT-EMS. The EMS is easily implementable, and considers quasi-constant cell energy extraction and filtering of current transients to the battery bank ensuring the longevity of the devices. A new mathematical model of the platform, a closed loop stability analysis, and numerical and Hardware-in-the-Loop (HIL) validations were presented. Some experimental validation results were also provided.
Optimal Generation Scheduling of Power System for Maximum Renewable Energy...IJECEIAES
This paper proposes an optimal generation scheduling method for a power system integrated with renewable energy sources (RES) based distributed generations (DG) and energy storage systems (ESS) considering maximum harvesting of RES outputs and minimum power system operating losses. The main contribution aims at economically employing RES in a power system. In particular, maximum harvesting of renewable energy is achieved by the mean of ESS management. In addition, minimum power system operating losses can be obtained by properly scheduling operating of ESS and controllable generations. Particle Swam Optimization (PSO) algorithm is applied to search for a near global optimal solutions. The optimization problem is formulated and evaluated taking into account power system operating constraints. The different operation scenarios have been used to investigate the effective of the proposed method via DIgSILENT PowerFactory software. The proposed method is examined with IEEE standard 14-bus and 30-bus test systems.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi-Objective Optimization Based Design of High Efficiency DC-DC Switching ...IJPEDS-IAES
In this paper we explore the feasibility of applying multi objective stochastic
optimization algorithms to the optimal design of switching DC-DC
converters, in this way allowing the direct determination of the Pareto
optimal front of the problem. This approach provides the designer, at
affordable computational cost, a complete optimal set of choices, and a more
general insight in the objectives and parameters space, as compared to other
design procedures. As simple but significant study case we consider a low
power DC-DC hybrid control buck converter. Its optimal design is fully
analyzed basing on a Matlab public domain implementations for the
considered algorithms, the GODLIKE package implementing Genetic
Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated
Annealing (SA). In this way, in a unique optimization environment, three
different optimization approaches are easily implemented and compared.
Basic assumptions for the Matlab model of the converter are briefly
discussed, and the optimal design choice is validated “a-posteriori” with
SPICE simulations.
A Review on Design and Development of high Reliable Hybrid Energy Systems wit...IJPEDS-IAES
Hybrid Energy system is a combination of two or more different types of energy resources. Now a day this hybrid energy system plays key role in various remote area power applications. Hybrid energy system is more reliable than single energy system. This paper deals with high reliable hybrid energy system with solar, wind and micro hydro resources. The proposed hybrid system cable of multi mode operation and high reliable due to non communicated based controllers (Droop Characteristic Control) are used for optimal power sharing. Size of battery can be reduced because hydro used as back up source and Maximum power point Tracking also applied to solar and wind energy systems.
Fuzzy logic control of hybrid systems including renewable energy in microgrids IJECEIAES
With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an effective, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is micro grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a fuzzy logic control of isolated hybrid systems (HRES) including renewable energy in micro-grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer.
Design methodology of smart photovoltaic plant IJECEIAES
In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
Economic Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Optimal Power Flow with Reactive Power Compensation for Cost And Loss Minimiz...ijeei-iaes
One of the concerns of power system planners is the problem of optimum cost of generation as well as loss minimization on the grid system. This issue can be addressed in a number of ways; one of such ways is the use of reactive power support (shunt capacitor compensation). This paper used the method of shunt capacitor placement for cost and transmission loss minimization on Nigerian power grid system which is a 24-bus, 330kV network interconnecting four thermal generating stations (Sapele, Delta, Afam and Egbin) and three hydro stations to various load points. Simulation in MATLAB was performed on the Nigerian 330kV transmission grid system. The technique employed was based on the optimal power flow formulations using Newton-Raphson iterative method for the load flow analysis of the grid system. The results show that when shunt capacitor was employed as the inequality constraints on the power system, there is a reduction in the total cost of generation accompanied with reduction in the total system losses with a significant improvement in the system voltage profile
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Power system operation considering detailed modelling of the natural gas supp...IJECEIAES
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
This paper focuses on the artificial bee colony (ABC) algorithm, which is a nonlinear optimization problem. is proposed to find the optimal power flow (OPF). To solve this problem, we will apply the ABC algorithm to a power system incorporating wind power. The proposed approach is applied on a standard IEEE-30 system with wind farms located on different buses and with different penetration levels to show the impact of wind farms on the system in order to obtain the optimal settings of control variables of the OPF problem. Based on technical results obtained, the ABC algorithm is shown to achieve a lower cost and losses than the other methods applied, while incorporating wind power into the system, high performance would be gained.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
In this paper a load flow based method using MATLAB Software is used to determine the optimum location and optimum size of DG in a 43-bus distribution system for voltage profile improvement and loss reduction. This paper proposes analytical expressions for finding optimal size of three types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. Single DG installation case was studied and compared to a case without DG, and 43-bus distribution system is used to demonstrate the effectiveness of the proposed method. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of injecting real power only, DG capable of injecting reactive power only and DG capable of injecting both real and reactive power can also be identified with their optimal size and location using the proposed method. This paper has been analysed with varying DG size and complexity and validated using analytical method for Summer case and Winter case in 43-bus distribution system in Myanmar.
Keywords- analytical method,distributed generation,power loss reduction,voltage profile improvement.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Harvesting in electric vehicles: Combining multiple power tracking and fuel-c...IJECEIAES
Exploitation of green energy sources is essential to diminish the deterioration of our environment. The energy harvesting, represents an alternative to achieve greater range in electric and hybrid vehicles. An energy management strategy (EMS) must be optimized to obtain the best benefits in such vehicles, which is not a trivial task. If harvesting or energy recovery devices are added, the EMS becomes a dual-purpose algorithm: minimizing fuel consumption and maximizing energy harvest through maximum power point tracking (MPPT) controllers. Known studies consider separate EMS, one for traction and another for regenerative braking, without considering harvest devices such as solar panels, regenerative suspension, thermal generators, among others. Furthermore, the electronic power converters used, are not designed to handle such unequal power levels. In this article, an electronic platform to include multiple energy harvesting devices in a fuel-cell hybrid electric vehicle, was presented together with a multiple MPPT-EMS. The EMS is easily implementable, and considers quasi-constant cell energy extraction and filtering of current transients to the battery bank ensuring the longevity of the devices. A new mathematical model of the platform, a closed loop stability analysis, and numerical and Hardware-in-the-Loop (HIL) validations were presented. Some experimental validation results were also provided.
Optimal Generation Scheduling of Power System for Maximum Renewable Energy...IJECEIAES
This paper proposes an optimal generation scheduling method for a power system integrated with renewable energy sources (RES) based distributed generations (DG) and energy storage systems (ESS) considering maximum harvesting of RES outputs and minimum power system operating losses. The main contribution aims at economically employing RES in a power system. In particular, maximum harvesting of renewable energy is achieved by the mean of ESS management. In addition, minimum power system operating losses can be obtained by properly scheduling operating of ESS and controllable generations. Particle Swam Optimization (PSO) algorithm is applied to search for a near global optimal solutions. The optimization problem is formulated and evaluated taking into account power system operating constraints. The different operation scenarios have been used to investigate the effective of the proposed method via DIgSILENT PowerFactory software. The proposed method is examined with IEEE standard 14-bus and 30-bus test systems.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi-Objective Optimization Based Design of High Efficiency DC-DC Switching ...IJPEDS-IAES
In this paper we explore the feasibility of applying multi objective stochastic
optimization algorithms to the optimal design of switching DC-DC
converters, in this way allowing the direct determination of the Pareto
optimal front of the problem. This approach provides the designer, at
affordable computational cost, a complete optimal set of choices, and a more
general insight in the objectives and parameters space, as compared to other
design procedures. As simple but significant study case we consider a low
power DC-DC hybrid control buck converter. Its optimal design is fully
analyzed basing on a Matlab public domain implementations for the
considered algorithms, the GODLIKE package implementing Genetic
Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated
Annealing (SA). In this way, in a unique optimization environment, three
different optimization approaches are easily implemented and compared.
Basic assumptions for the Matlab model of the converter are briefly
discussed, and the optimal design choice is validated “a-posteriori” with
SPICE simulations.
A Review on Design and Development of high Reliable Hybrid Energy Systems wit...IJPEDS-IAES
Hybrid Energy system is a combination of two or more different types of energy resources. Now a day this hybrid energy system plays key role in various remote area power applications. Hybrid energy system is more reliable than single energy system. This paper deals with high reliable hybrid energy system with solar, wind and micro hydro resources. The proposed hybrid system cable of multi mode operation and high reliable due to non communicated based controllers (Droop Characteristic Control) are used for optimal power sharing. Size of battery can be reduced because hydro used as back up source and Maximum power point Tracking also applied to solar and wind energy systems.
Fuzzy logic control of hybrid systems including renewable energy in microgrids IJECEIAES
With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an effective, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is micro grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a fuzzy logic control of isolated hybrid systems (HRES) including renewable energy in micro-grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer.
Optimal Configuration of Wind Farms in Radial Distribution System Using Parti...journalBEEI
Recently, a wide range of wind farm based distributed generations (DGs) are being integrated into distribution systems to fulfill energy demands and to reduce the burden on transmission corridors. The non-optimal configuration of DGs could severely affect the distribution system operations and control. Hence, the aim of this paper is to analyze the wind data in order to build a mathematical model for power output and pinpoint the optimal location. The overall objective is minimization of power loss reduction in distribution system. The five years of wind data was taken from 24o 44’ 29” North, 67o 35’ 9” East coordinates in Pakistan. The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. The result reveals that the proposed method helps in improving renewable energy near to load centers, reduce power losses and improve voltage profile of the system. Moreover, the validity and performance of the proposed model were also compared with other optimization algorithms.
Stochastic control for optimal power flow in islanded microgridIJECEIAES
The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model.
Impact of compressed air energy storage system into diesel power plant with w...IJECEIAES
The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.
Overall fuzzy logic control strategy of direct driven PMSG wind turbine conne...IJECEIAES
The fuzzy logic strategies reported in the literature about the control of direct drive permanent magnet synchronous generator (PMSG) connected to grid are limited in terms of inclusiveness and efficiency. So an overall control based on fuzzy logic and anti-windup compensation is proposed in this paper. Aiming at the inadequate of hill climb search (HCS) MPPT with fixed step size, the fuzzy logic is introduced in the stage of "generating rotor speed reference" to overcome the oscillations and slowness in traditional method. PI controllers are replaced by anti-windup fuzzy logic controllers in the "machine side control" stage and in "grid side control" stage to pertinently regulate the reference parameters. Then comparison tests with classical methods are implemented under varying climatic conditions. The results obtained demonstrate that the developed control is superior to other methods in response time (less than 4.528E-04 s), precision (an overshoot about 0.41%) and quality of produced energy (efficiency is 91%). The study verifying the feasibility and effectiveness of this algorithm in PMSG wind turbine connected to grid.
optimization of the managed electrical energy within a hybrid renewable energ...INFOGAIN PUBLICATION
Hybrid energy applications based on renewable energy sources are becoming more and more desirable every day. They have increased the economic attractiveness of renewable electric energy generation. Because of the sudden fluctuations of the load requirements, the main attribute of such Hybrid Systems is to be able to generate energy at any time by optimally using each source. In this article, we have proposed a combination between a sizing study and a control one for the aim of solving the complex optimization problem of finding the optimal combination of size and storage to make the best use of the renewable power generations and to become more independent of rising electricity costs. Additionally, an improvement in the induced optimization algorithm is introduced in this paper so as to compute the optimal size and the operation control of the system with the aim of minimizing as much as possible the cost while responding to the load energy requirements taking into account the environmental factors.
Loss issue is significant in power system since it affects the operation of power system, which ultimately can be translated to monetary effect. Incremental demand that explicitly adding the reactive load causes extra heating losses in the transmission circuit. Without appropriate remedial control, the temperature increase on transmission line cable would end with insulation failure. This phenomenon can be alleviated with a proper compensation scheme that provides optimal solution along with avoidance of under-compensation or over-compensation. Evolutionary Programming (EP) has been recognised as one of the powerful optimisation technique, applied in solving power system problems. Nevertheless, EP is an old technique that sometimes could reach to a settlement that is not fully satisfied. Thus, the need fora new approach to improve the setback is urgent. This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment. The classical EP was integrated with immune algorithm so as to reduce the computational burden experienced by the classical EP.The algorithm has been tested on an IEEE 12-Bus System and IEEE 14-Bus System.Comparative study was conducted between EP and IEP in terms of optimisation performance. The optimal size and location of PV determined by IEP was able to control the loss in transmission system when the load increases. Results obtained from the studies revealed the merit of the proposed IEP; indicating its feasibility for future implementation in practical system.
Similar to Solution for optimal power flow problem in wind energy system using hybrid multi objective artificial physical optimization algorithm (20)
The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.
This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
Kosovo has limited renewable energy resources and its power generation sector is based on fossil fuels. Such a situation emphasizes the importance of active research and efficient use of renewable energy potential. According to the analysis of meteorological data for Kosovo, it can be concluded that among the most attractive potential wind power sites are the locations known as Kitka (42° 29' 41" N and 21° 36' 45" E) and Koznica (42° 39′ 32″ N, 21° 22′30″E). The two terrains in which the analysis was carried out are mountain areas, with altitudes of 1142 m (Kitka) and 1230 m (Koznica). the same measuring height, about 84 m above the ground, is obtained for these average wind speeds: Kitka 6,667 m/s and Koznica 6,16 m/s. Since the difference in wind speed is quite large versus a difference in altitude that is not being very large, analyses are made regarding the terrain characteristics including the terrain relief features. In this paper it will be studied how much the roughness of the terrain influences the output energy. Also, that the assumption to be taken the same as to how much they will affect the annual energy produced.
Large-scale grid-tied photovoltaic (PV) station are increasing rapidly. However, this large penetration of PV system creates frequency fluctuation in the grid due to the intermittency of solar irradiance. Therefore, in this paper, a robust droop control mechanism of the battery energy storage system (BESS) is developed in order to damp the frequency fluctuation of the multi-machine grid system due to variable active power injected from the PV panel. The proposed droop control strategy incorporates frequency error signal and dead-band for effective minimization of frequency fluctuation. The BESS system is used to consume/inject an effective amount of active power based upon the frequency oscillation of the grid system. The simulation analysis is carried out using PSCAD/EMTDC software to prove the effectiveness of the proposed droop control-based BESS system. The simulation result implies that the proposed scheme can efficiently curtail the frequency oscillation.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
This paper focuses on the modeling and control of a wind energy conversion chain using a permanent magnet synchronous machine. This system behaves a turbine, a generator, DC/DC and DC/AC power converters. These are connected on both sides to the DC bus, where the inverter is followed by a filter which is connected to the grid. In this paper, we have been used two types of controllers. For the stator side converter, we consider the Takagi-Sugeno approach where the parameters of controller have been computed by the theory of linear matrix inequalities. The stability synthesis has been checked using the Lyapunov theory. According to the grid side converter, the proportional integral controller is exploited to keep a constant voltage on the DC bus and control both types of powers. The simulation results demonstrate the robustness of the approach used.
The development of modeling wind speed plays a very important in helping to obtain the actual wind speed data for the benefit of the power plant planning in the future. The wind speed in this paper is obtained from a PCE-FWS 20 type measuring instrument with a duration of 30 minutes which is accumulated into monthly data for one year (2019). Despite the many wind speed modeling that has been done by researchers. Modeling wind speeds proposed in this study were obtained from the modified Rayleigh distribution. In this study, the Rayleigh scale factor (Cr) and modified Rayleigh scale factor (Cm) were calculated. The observed wind speed is compared with the predicted wind characteristics. The data fit test used correlation coefficient (R2), root means square error (RMSE), and mean absolute percentage error (MAPE). The results of the proposed modified Rayleigh model provide very good results for users.
This paper deals with an advanced design for a pump powered by solar energyto supply agricultural lands with water and also the maximum power point is used to extract the maximum value of the energy available inside the solar panels and comparing between techniques MPPT such as Incremental conductance, perturb & observe, fractional short current circuit, and fractional open voltage circuit to find the best technique among these. The solar system is designed with main parts: photovoltaic (PV) panel, direct current/direct current (DC/DC) converter, inverter, filter, and in addition, the battery is used to save energy in the event that there is an increased demand for energy and not to provide solar radiation, as well as saving energy in the case of generation more than demand. This work was done using the matrix laboratory (MATLAB) simulink program.
The objective of this paper is to provide an overview of the current state of renewable energy resources in Bangladesh, as well as to examine various forms of renewable energies in order to gain a comprehensive understanding of how to address Bangladesh's power crisis issues in a sustainable manner. Electricity is currently the most useful kind of energy in Bangladesh. It has a substantial influence on a country's socioeconomic standing and living standards. Maintaining a stable source of energy at a cost that is affordable to everyone has been a constant battle for decades. Bangladesh is blessed with a wealth of natural resources. Bangladesh has a huge opportunity to accelerate its economic development while increasing energy access, livelihoods, and health for millions of people in a sustainable way due to the renewable energy system.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
A stable operation of wind turbines connected to the grid is an essential requirement to ensure the reliability and stability of the power system. To achieve such operational objective, installing static synchronous compensator static synchronous compensator (STATCOM) as a main compensation device guarantees the voltage stability enhancement of the wind farm connected to distribution network at different operating scenarios. STATCOM either supplies or absorbs reactive power in order to ensure the voltage profile within the standard-margins and to avoid turbine tripping, accordingly. This paper present new study that investigates the most suitable-location to install STATCOM in a distribution system connected wind farm to maintain the voltage-levels within the stability margins. For a large-scale squirrel cage induction generator squirrel-cage induction generator (SCIG-based) wind turbine system, the impact of STATCOM installation was tested in different places and voltage-levels in the distribution system. The proposed method effectiveness in enhancing the voltage profile and balancing the reactive power is validated, the results were repeated for different scenarios of expected contingencies. The voltage profile, power flow, and reactive power balance of the distribution system are observed using MATLAB/Simulink software.
The electrical and environmental parameters of polymer solar cells (PSC) provide important information on their performance. In the present article we study the influence of temperature on the voltage-current (I-V) characteristic at different temperatures from 10 °C to 90 °C, and important parameters like bandgap energy Eg, and the energy conversion efficiency η. The one-diode electrical model, normally used for semiconductor cells, has been tested and validated for the polemeral junction. The PSC used in our study are formed by the poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl C61-butyric acid methyl ester (PCBM). Our technique is based on the combination of two steps; the first use the Least Mean Squares (LMS) method while the second use the Newton-Raphson algorithm. The found results are compared to other recently published works, they show that the developed approach is very accurate. This precision is proved by the minimal values of statistical errors (RMSE) and the good agreement between both the experimental data and the I-V simulated curves. The obtained results show a clear and a monotonic dependence of the cell efficiency on the studied parameters.
The inverter is the principal part of the photovoltaic (PV) systems that assures the direct current/alternating current (DC/AC) conversion (PV array is connected directly to an inverter that converts the DC energy produced by the PV array into AC energy that is directly connected to the electric utility). In this paper, we present a simple method for detecting faults that occurred during the operation of the inverter. These types of faults or faults affect the efficiency and cost-effectiveness of the photovoltaic system, especially the inverter, which is the main component responsible for the conversion. Hence, we have shown first the faults obtained in the case of the short circuit. Second, the open circuit failure is studied. The results demonstrate the efficacy of the proposed method. Good monitoring and detection of faults in the inverter can increase the system's reliability and decrease the undesirable faults that appeared in the PV system. The system behavior is tested under variable parameters and conditions using MATLAB/Simulink.
The electrical distribution network is undergoing tremendous modifications with the introduction of distributed generation technologies which have led to an increase in fault current levels in the distribution network. Fault current limiters have been developed as a promising technology to limit fault current levels in power systems. Though, quite a number of fault current limiters have been developed; the most common are the superconducting fault current limiters, solid-state fault current limiters, and saturated core fault current limiters. These fault current limiters present potential fault current limiting solutions in power systems. Nevertheless, they encounter various challenges hindering their deployment and commercialization. This research aimed at designing a bridge-type nonsuperconducting fault current limiter with a novel topology for distribution network applications. The proposed bridge-type nonsuperconducting fault current limiter was designed and simulated using PSCAD/EMTDC. Simulation results showed the effectiveness of the proposed design in fault current limiting, voltage sag compensation during fault conditions, and its ability not to affect the load voltage and current during normal conditions as well as in suppressing the source powers during fault conditions. Simulation results also showed very minimal power loss by the fault current limiter during normal conditions.
This paper provides a new approach to reducing high-order harmonics in 400 Hz inverter using a three-level neutral-point clamped (NPC) converter. A voltage control loop using the harmonic compensation combined with NPC clamping diode control technology. The capacitor voltage imbalance also causes harmonics in the output voltage. For 400 Hz inverter, maintain a balanced voltage between the two input (direct current) (DC) capacitors is difficult because the pulse width modulation (PWM) modulation frequency ratio is low compared to the frequency of the output voltage. A method of determining the current flowing into the capacitor to control the voltage on the two balanced capacitors to ensure fast response reversal is also given in this paper. The combination of a high-harmonic resonator controller and a neutral-point voltage controller working together on the 400 Hz NPC inverter structure is given in this paper.
Direct current (DC) electronic load is a useful equipment for testing the electrical system. It can emulate various load at a high rating. The electronic load requires a power converter to operate and a linear regulator is a common option. Nonetheless, it is hard to control due to the temperature variation. This paper proposed a DC electronic load using the boost converter. The proposed electronic load operates in the continuous current mode and control using the integral controller. The electronic load using the boost converter is compared with the electronic load using the linear regulator. The results show that the boost converter able to operate as an electronic load with an error lower than 0.5% and response time lower than 13 ms.
This paper presents a new simplified cascade multiphase DC-DC buck power converter suitable for low voltage and large current applications. Cascade connection enables very low voltage ratio without using very small duty cycles nor transformers. Large current with very low ripple content is achieved by using the multiphase technique. The proposed converter needs smaller number of components compared to conventional cascade multiphase DC-DC buck power converters. This paper also presents useful analysis of the proposed DC-DC buck power converter with a method to optimize the phase and cascade number. Simulation and experimental results are included to verify the basic performance of the proposed DC-DC buck power converter.
More from International Journal of Power Electronics and Drive Systems (20)
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
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Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
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Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
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Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
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follows that, the grid integrated wind powered units, may introduce severe challenges to traditional
generation scheduling methodologies and operation of power system [8]. For satisfactory grid integration, the
wind power fluctuation may have to be balanced by other types of generation. Alternatively, to compensate
for the power imbalance due to uncertainty of wind, additional cost may have to be added with the total
power generation cost of the system [9].
The major goal of Optimal Power Flow (OPF) is to improve a target capacity such as cost of fuel by
means of ideal change of the control variables simultaneously different equality and inequality constraints.
For the main intend of economical and secure operation and planning of power systems, optimal power flow
(OPF) is employed [10]. The objective of OPF is to reduce the cost of fuel, environmental pollution and also
the power lost by the network. In power system economic load dispatch (ELD) is commonly used to find
generation or fuel cost. The major goal of Economic Dispatch (ED) is to minimize the amount of total
pollution caused by the environment. This can be done by avoiding the burning of fuels [11]. Economic Load
Dispatch (ELD) is determined as the technique in which the generation levels are allocated to the generating
units. As a result the load of the system is totally and economically supplied. The ELD is a large-scale, highly
non-linear, constrained optimization problem [12]. The main aim of ELD is conflicting in nature and to
achieve an acceptable strategy of power dispatch within different system constraints and also it helps to keep
the pollution within the limits and it reduces the fuel cost [13].
Application with renewable energy sources such as solar cell array, wind turbines, or fuel cells have
increased significantly during the past decade. To obtain the clean energy, we are using the hybrid solar-wind
power generation. Consumers prefer quality power from suppliers. The quality of power can be measured by
using parameters such as voltage sag, harmonic and power factor. To obtain quality power we have different
topologies. In our paper we present a new possible topology which improves power quality [14].
The hybrid power system is normally equipped with control system which functions to reduce the
system frequency oscillations and makes the wind turbine generator power output follow the performance
curve when the system is subjected to wind/load disturbances. Usually PI controllers are employed in these
systems. Unfortunately since the operating point changes depending on the demand of consumers, this
constant gain PI controller are unsuitable to other operating points. Therefore, it describes the application of
fuzzy gain scheduling of PI controller for an isolated wind-diesel hybrid power system with superconducting
magnetic energy storage [15].
Reduction of operating costs in power system in order to return the investment costs and more
profitability has vital importance in power industry. Economic Load Dispatch (ELD) is one of the most
important issues in reducing operating costs. ELD is formulated as a nonlinear optimization problem with
continuous variables within the power plants. The main purpose of this problem is optimal planning of power
generation in power plants with minimum cost by total units, regarded to equality and inequality constraints
including load demand and the range of units' power productivity. In this article, Economic Load Dispatch
problem has been modeled by considering the valve-point loading effects with power plants' constraints such
as: the balance of production and consumption in system, the forbidden zones, range of production,
increasing and decreasing rates, reliability constraints and network security [16].
In recent years wind turbine technology has undergone rapid developments, growth in size. The
wind energy become increasingly competitive with conventional energy sources based on the optimization of
wind turbines. The penetration of wind energy in the grid raises questions about the compatibility of the wind
turbine power production with the grid. In particular, the contribution to grid stability, power quality and
behavior during fault situations plays therefore as important a role as the reliability. In this paper, a vector
control scheme is developed to control the rotor side voltage source converter [17].
A new control method for quasi-Z-source cascaded multilevel inverter-based grid-connected
photovoltaic (PV) system is proposed. The proposed method is capable of boosting the PV array voltage to a
higher level and solves the imbalance problem of DC-link voltage in traditional cascaded H-bridge inverters.
This system adjusts the grid injected current in phase with the grid voltage and achieves independent
maximum power point tracking (MPPT) for the separate PV arrays. To achieve these goals, the proportional-
integral (PI) controllers are employed for each module. For achieving the best performance, this paper
presents an optimum approach to design the controller parameters using particle swarm optimization (PSO).
The primary design goal is to obtain good response by minimizing the integral absolute error. Also, the
transient response is guaranteed by minimizing the overshoot, settling time and rise time of the system
response. The effectiveness of the new proposed control method has been verified through simulation studies
based on a seven level quasi-Z-Source cascaded multilevel inverter [18].
Embellished Particle Swarm Optimization is to extend the single population PSO to the interacting
multi-swarm model. Through this multi-swarm cooperative approach, diversity in the whole swarm
community can be upheld. Concurrently, the swarm-to-swarm mechanism drastically speeds up the swarm
community to converge to the global near optimum. In order to evaluate the performance of the proposed
3. ISSN: 2088-8694
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488
algorithm, it has been tested in standard IEEE 57,118 bus systems and results show that Embellished Particle
Swarm Optimization (EPSO) is more efficient in reducing the Real power losses when compared to other
standard reported algorithms [19].
The problem of Optimal Power Flow can be solved by utilizing various techniques like linear
programming, non-linear programming, interior-point technique, quadratic programming, sequential
unconstrained minimization and Newton based techniques and also it can be solved by the integration of
optimization techniques like evolutionary programming (EP), particle swarm optimization (PSO), and
sequential quadratic programming (SQP)[20]. There are two steps involved. In the first step, the solution
space is investigated by both EP and PSO techniques. In the second step, SQP is utilized when there is a
development in the result of first phase [21]. EP is a kind of global searching technique. It begins at the
population of candidate solution and at last evaluation process is utilized to find the near global solution in
parallel. GA is a search algorithm based on the mechanics of natural genetics and natural selection. The
evolution procedure of organs with functional optimizations is integrated here. Reproduction, crossover and
mutation are the three basic prime operators associated with GA. Based on the chromosomes, GA works. A
set of binary digits which describes the control parameter coding is contained in these chromosomes which is
composed themselves with genes [22], [23].
It is necessary to control the power flow at the optimal range while the renewable energy sources are
used in power systems. The main contribution of this paper is i) To formulate the optimal power flow
problem as a multi objective optimization problem ii) And to utilize the Artificial Physical Optimization
(APO) algorithm with Animal migration optimization as a solution to the OPF problem. The remainder of
this paper is organized as follows: Some of the recent related researches to our proposed method is explained
in section 2. The proposed methodology with problem formulation is explained in section 3. The
Experimental results of the proposed method and the comparison with existing methods are presented in
section 4 followed by the conclusion in section 5.
2. RELATED WORKS
Some of the recent research work related to the OPF problem in wind energy system is listed
as follows:
Shanhe Jiang et.al [24] introduced “A hybrid particle swarm optimization and gravitational search
algorithm for solving economic emission load dispatch problems with various practical constraints”. To solve
economic emission load dispatch problem, in this paper PSO was integrated with GSA. Both the utilized
approach was based on population. In PSO technique, the agents were taken as particle. Here the movement
of each particle was based on both the past best solution of its own and the past best solution of its group. In
GSA, the agents were taken as objects. Here the one object was fascinated by other objects through
gravitational force. The agent in GSA was described through four types of parameters. The first parameter
was the position of the mass in which solution to the problem was stated at specified search space. The
second parameter was the inertial mass which decelerates its motion by reflection of its resistance. The third
and fourth parameter was the active and passive gravitational mass. The estimation of both gravitational and
inertial mass was done through fitness function. Both the algorithms were integrated by any one of the two
procedures. (i.e.) one work starts after the completeness of the previous work and the other way was to
employ co-evolutionary method to consider the swarm components as the components introduced by
PSO-GSA.
Aniruddha Bhattacharya and Pranab Kumar Chattopadhyay [25] developed “Hybrid Differential
Evolution with Biogeography-Based Optimization for Solution of Economic Load Dispatch”. Here the issue
of both convex and non-convex economic load dispatch was solved by the combination of differential
evolution (DE) algorithm and biogeography-based optimization algorithm. The above combination of
algorithms also solves problems like degradation of solution quality and low speed. The DE algorithm was
based on population. Here functions like non-differentiable, nonlinear and multi-modal objective can be
handled and a trial vector was constructed by each parent individual in order to produce new offspring. There
were three types of basic operators was involved to enhance the population namely mutation, crossover, and
selection. In Biogeography activities like the movement of one island to another, appearance and
disappearance of new species were expressed. The quality of the solution will be degraded in later stage due
to the existence of cross-over operation in evolutionary based algorithm whereas in BBO, cross-over
operation was not restricted.
IejinCai et.al [26] presented “A hybrid CPSO–SQP method for economic dispatch considering the
valve-point effects”. In this paper, chaotic particle swarm optimization (CPSO) algorithm and sequential
quadratic programming (SQP) were incorporated to retrieve the solution for economic power dispatch
problem. Here the central optimizer was the CPSO and to enhance quality of the solution, the results were
4. Int J Pow Elec & Dri Syst ISSN: 2088-8694
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adjusted by SQP. The CPSO was designed based on tent equation. CPSO was a combination of PSO and
CLS. Where global exploration was carried out in PSO and local search was done to the solutions of the PSO
through CLS. IN SQP, there were three stages. In the first stage, the Hessian matrix contained in the
lagrangian function was updated. Estimation of line search and merit function was done at the second stage
and finally solution was acquired for the problem of quadratic programming. The optimal power generation
of each unit which was submitted to operation was found by the hybridization of CPSO-SQP technique.
Behnam Mohammadi-Ivatloo et.al [27] discussed “Nonconvex Dynamic Economic Power Dispatch
Problems Solution Using Hybrid Immune-Genetic Algorithm”. The cost needed for operation was reduced
and also the solution for the problem of dynamic economic dispatch (DED) in a non-convex solution space
was found by the consolidation of immune algorithm (IA) and genetic algorithm (GA). In IA, when the
extraneous molecules was arrived in the immune system of human body a reaction occurs. Even though this
algorithm does not contain any knowledge about that molecule, they were analyzed by this algorithm after
some time and also solution for the removal of these molecules was found. Here the extraneous molecule was
known as antigens and the reaction of the immune system was known as antibodies. The antibodies should be
balanced with the unknown antigens. The antibodies were given by the objective function, its combined
constraints from the antigens and the solutions which enhance them. Some antibodies was generated by the
human body at the initial stage and those antibodies was compared with the newcomer antigens and the
identical properties between them was estimated. This estimation was known as affinity factor.
K. Vaisakh et.al [28] designed “Solving dynamic economic dispatch drawback with security
constraints exploitation bacterial forage PSO-DE algorithm”. Here problems like non-smooth, non-convex
nature attributable to valve-point loading effects, ramp rate limits, spinning reserve capability, prohibited in
operation zones and security constraints was shown in DED drawback. The on top of mentioned issues is
often defeated by the mixing of bacterial forage Particle Swarm improvement (BPSO) with differential
evolution (DE) algorithmic rule. The BPSO was a mixture of microorganism forage optimization algorithmic
rule and PSO. The bacterium with positive foraging methods was chosen by the PSO operator within the
change method of each chemo-tactic step, so as to get reduced price. In our new BPSO-DE approach, the
primary step was the substitution of velocity in place of delta. Within the second step, through the calculation
of fitness operate the population of best fitness within the current generation and also the worth for world
best fitness was obtained. Within the third step, the position of generation was modified to a replacement
position. Within the fourth step, to retrieve the losses from power, apparent power within the lines and
voltages of load was retrieved by the load flow operation that was done with those new populations made at
the previous step. Within the fifth step the violations was verified for the line flows and cargo voltages. If it
contains violations then penalty terms were additional to the fitness operate of each BPSO and Delaware.
Each the fitness functions were compared for each bacterial population and also the best worth was keeping
in an exceedingly separate variable. The simplest value of fitness, real power generation price, voltages, line
flows, power losses for the given interval were updated for all the microorganism population as pbest and
global best (gbest). Then the procedure for next chemo-tactic step was continual.
3. PROPOSED OPTIMIZATION SOLUTION TO OPF PROBLEM
In a wind energy system, Optimal Power Flow (OPF) is a Multi-objective optimization problem that
seeks to find out a compromise solution to minimize the fuel cost, power loss, emission and
maintaining voltage stability. The Solution of optimal power flow (OPF) problem aims to optimize a selected
objective function through optimal adjustment of the power system control variables while at the same time
satisfying the various equality and inequality constraints. According to the results of previous investigations,
Animal Migration Optimization (AMO) and Artificial Physical Optimization (APO) have better performance
for solving optimizations problems. In this work, we intend to propose a Hybrid Multi objective Artificial
Physical Optimization (HMOAPO) is to solving the OPF (Optimal Power Flow) problem in wind energy
system. The architecture of our proposed work is shown in Figure 1.
5. ISSN: 2088-8694
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cv
Animal migration
with artificial
physical
optimization
Adaptive penalty
function
Hybrid optimization for optimal power flow control
Figure 1. Architecture of our proposed work
To enhance the performance of APO, this work applies an Animal Migration algorithm (AMO)
which follows three main rules for each individual and also to overcome the drawback of premature
convergence. In addition, the MOAPO is combined with Adaptive Penalty Function to handle equality and
inequality constrains associated with OPF problems. The adaptive penalty function (APF), which convert a
constrained problem into an unconstrained one where the ‘Penalty Function’ penalize the infeasible solutions
to move towards desirable feasible solutions.
3.1. OPF problem definition
The OPF problem is considered as a general optimization problem. The OPF problem expects to
reduce the whole fuel cost perform whereas fulfilling the whole load, completely different equality and
difference constraints. Likewise, the best values of the management variables within the power grid are
resolved within the OPF problem. Mathematical expression belonging to the matter is delineating as follows.
T
OF
OF
OF
OF
OF
OF
Min )
,
,
,
,
,
( 6
5
4
3
2
1
(1)
Subject to:
,
sin
cos
|
|
|
|
1
ij
ij
ij
ij
N
j
j
i
Di
Gi
B
G
V
V
P
P
,
N
i
(2)
,
cos
sin
|
|
|
|
1
N
j
ij
ij
ij
ij
j
i
Di
Ci
Gi
B
G
V
V
Q
Q
Q
,
N
i
(3)
,
,
max
min
g
Gi
Gi
Gi
N
i
P
P
P
(4)
,
,
max
min
g
Gi
Gi
Gi N
i
Q
Q
Q
(5)
,
|,
|
|
|
|
| max
min
N
i
V
V
V i
i
i
(6)
,
,
max
min
t
k
k
k
N
k
t
t
t
(7)
,
, nbr
i
S
S rated
li
li
(8)
,
,
max
min
c
ci
ci
ci N
i
Q
Q
Q
(9)
1
sin
|
|
4
2
j
i
i
j
ij
ij
V
Q
X
LSI
(10)
6. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Solution for optimal power flow problem in wind energy system using hybrid... (P. Nagaleshmi)
491
,
tan 1
ij
ij
R
X
(11)
.
sin
|
|
|
|
sin
|
|
|
||
| 2
ij
j
j
i
ij
j
i
j
Z
V
Z
V
V
Q
(12)
In this work, the target perform of the OPF problem is proposed because the total generation value
as well as valve-point impact, loss minimization and prohibited zones. The power flow equations are
thought-about because the equality constraints. The transmission limits and alternative security limits are
used as difference constraints. The vectors are outlined as state variable and control variable vectors are
outlined as follows:
.
........
,
........
,
.......
,
...... 1
1
1
1 Nc
c
c
Nt
Ng
g
g
Ng
g
g
Q
Q
T
T
V
V
P
P
(13)
Where g
P , g
V , Nt
T , c
Q are described as the active power of the slack bus, the voltage magnitude of
the load buses, active power output of the generators except at the slack bus, the reactive power of the
generators respectively.
.
......
,
.......
,
...... 1
1
1 nbr
PQ l
l
N
PQ
PQ
Ng
g
g S
S
V
V
Q
Q
(14)
Where g
Q , PQ
V and l
S are defined as the reactive power generation at bus, the voltage of load bus
and the line flow, respectively.
Objective function
In this paper, the objective function of the OPF problem is defined as minimization of the total fuel
cost of the power generation system. The total fuel cost can be mathematically defined as follows:
Ng
i
i
Gi
i
Gi
i
c
P
b
P
a
OF
1
2
1
(15)
Where i
PG are represented as the active power output of the
th
i generator, respectively. i
a , i
b
and i
c are the fuel cost coefficients of the
th
i generator.
3.2. The generation cost minimization with valve point loading (VPL) effect
The generation cost with valve-point effect is presented as follows:
Gi
Gi
i
i
Ng
i
i
Gi
i
Gi
i
P
P
e
d
c
P
b
P
a
OF
min
1
2
2
sin (16)
Where i
d and i
e are coefficients of the valve-point effect of the
th
i generator. Typical curve
related to fuel cost with and without valve-point effect of the generation units is shown in Figure2.
Unit
Cost
With valve point effect
Without valve point effect
Figure 2. Typical curve related to fuel cost with and without valve-point effect of the generation units
7. ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 10, No. 1, March 2019 : 486 – 503
492
Let
k
j
W
k
j P
W ,
,
be the electrical energy cost of wind power of the th
j wind farm and the
th
k wind
power generator. Therefore, the cost of the wind unit can be defined by:
k
j
k
j
k
j
z
k
j
k
j
k
j
z
k
j
k
j
k
j
W
k
j P
P
P
P
P
P
W ,
,
,
,
,
,
,
,
,
,
,
,
~
ˆ
~
2
1
(17)
Which, k
j
k
j
P
P ,
,
~
,
are expected and available generation output of the unit j in the wind farm k (MW).
k
j,
, k
j
z ,
,
1
and k
j
z ,
,
2
are namely direct, overestimation and underestimation electrical wind energy cost
coefficient of the unit j in the wind farm k ($/MWh).
3.3. Generating units with prohibited operating zones (POZs)
The physical limitations of the power plant components, prohibited operating zones (POZs) are
occurred in a hydro-generating unit. This constraint dictates several feasible sub-regions for hydro-generating
units as shown in Figure 3 and can be expressed by:
Valve
point
effect
Prohibited
zone
Cost
The unit
th
i
k
LB
i
P
1
k
UB
i
P
Figure 3. Topology of cost function with prohibit zone constraint and valve point effect
k
g
i
i
UB
i
LB
i
i
UB
i
LB
i
i
i
N
k
N
i
P
P
P
P
P
P
P
P
P
k
k
k
,.....,
2
,
1
,
,......,
2
,
1
,
max
min
1
1
(18)
Which, 1
k
UB
i
P and k
LB
i
P are upper and lower limits of the
th
k sub-regions of the
th
i unit, respectively.
g
N and k
N are the number of thermal units and sub-regions.
Power Loss Minimization
The total real power loss in power systems is represented by
N
i
N
j
j
i
j
i
ij
j
i
j
i
ij
Q
P
P
Q
Q
Q
P
P
OF
1 1
3
(19)
Which
j
i
j
i
ij
ij
j
i
j
i
ij
ij
V
V
r
V
V
r
sin
,
cos
, i
i
V
is the complex voltage at the bus
th
i . ij
ij
ij
jx
r
Z
is the
th
ij element of [Zbus] impedance matrix. i
P and j
P are the active power injections at the
th
i and th
j buses,
respectively. i
Q and j
Q are the reactive power injections at the
th
i and th
j buses, respectively. N is the
number of buses.
L-index minimization
The voltage stability index (VSI) which ensures secure operations and is written as follows
8. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Solution for optimal power flow problem in wind energy system using hybrid... (P. Nagaleshmi)
493
and
V
V
V
dV
V
V
OF avg
N
i
avg
i
2
|
|
|
|
,
|
| min
max
1
4
(20)
,
2
|
| min
max
V
V
dV
(21)
Where n is selected to be equal 1.Finally, wind power can be expressed by the piecewise linear
as follows:
f
w
k
j
co
k
j
k
j
h
k
j
h
k
j
k
j
k
j
k
j
k
j
k
j
k
j
k
j
k
j
ci
k
j
k
j
k
j
k
j
k
j
k
j
k
j
k
j
k
j
ci
k
j
k
j
k
j
k
j
k
j
ci
k
j
k
j
k
j
h
k
i
N
k
N
j
otherwise
T
T
T
T
T
T
T
T
D
T
T
D
T
T
D
T
T
T
T
T
D
T
T
D
T
T
T
T
D
P
P
,...
2
,
1
,
,...
2
,
1
,
0
,
1
),
(
)
(
)
(
),
(
)
(
,
,
,
,
,
,
,
,
,
2
,
,
2
,
,
,
3
,
,
1
,
,
2
,
,
2
,
,
,
,
1
,
,
1
,
,
2
,
,
,
1
,
,
1
,
,
,
2
,
,
,
,
1
,
,
1
,
,
1
,
,
,
,
,
,
1
,
,
,
(22)
Which, Di,j,k is slope of section j of the wind unit w in wind farm f (MWs/m). Tci,j,k, Tco,j,k, Ti,j,k
and Th,j,k are cut-in wind speed, cut-out wind speed, breakpoint of segment i and rated wind speed, for all
the wind units w in the wind farm (m/s), respectively.
Artificial Physical Optimization
APO is a nature-inspired metaheuristic method inspired by natural physical forces based on artificial
physics (AP) framework [29]which is developed by Spear et al. Based on the similarity among the AP
method and population-based optimization algorithm, recently some authors proposed APO and tested its
optimization performance [30–32]. APO can be described briefly as follows
Assume the optimization problem can be expressed as
D
d
x
x
x
t
s
x
f
d
d
d
d
,........,
2
,
1
,
.
.
)
(
min
max
min
Where D is the dimension of the problem, d
xmin
and
d
xmax are the minimum and maximum limits of
variable
d
x .
The particle’s position signifies the solution to the optimization problem. The position of particle i
is defined as
.
,.........
2
,
1
,
,.......,
,.......,
, 2
1
NP
i
x
x
x
x
X D
i
d
i
i
i
i
Where NP is the number of individuals in APO;
d
i
x is the position of the
th
i individual in
th
d
dimension.
Step 1: Population Initialization.
The NP individual’s positions are randomly formed in the n-dimensional decision space.
The NP individual’s velocities are set to be zero.
Step 2: Fitness calculation.
Compute the fitness of each individual according to the objective function.
Step 3: Force calculation.
In the APO, the process of optimization is continuously performed by moving the individual toward
the promising region until the optimal solutions is found. And the rules for moving the individuals are
decided by the forces act on each other. The rules can be expressed by the following equations:
4. SIMULATION RESULTS AND COMPARISONS
The proposed algorithm is developed using MATLAB version 6.5 programming language and the
proposed methodology is tested in IEEE 30-bus system and the samples are tested on 2.6-Ghz Pentium-IV
PC. The generators data and cost coefficients are gathered from [25].
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494
4.1. Case studies on the IEEE 30-bus System
4.1.1. Comparison with global optimization
Initially the sample is tested in IEEE 30-bus, 41-branch system with the voltage constraint of lower
and upper limits are 0.9 p.u and 1.1 p.u., respectively. The APO population size is taken equal 30, the most
range of generation is 100, and crossover and mutation are applied with initial likelihood zero.9 and 0.01
severally. Figure 4 shows the topology of normal IEEE 30 bus system.
Figure 4. IEEE 30 bus system
For the aim of supportive the efficiency of the proposed approach, we have a tendency to created a
comparison of our efficiency with others competitive OPF efficiency. In [25], they conferred a typical GA, in
[3] the authors conferred associate enhanced GA, and so in [26], they proposed an Improved evolutionary
programming (IEP). In [27] they presented an optimum power flow solution using GA-Fuzzy system
approach (FGA), and in [11] a changed differential evolution is proposed (MDE). The budget items in our
proposed approach is 800.8336 and therefore the power loss is 8.92 that area unit higher than the others
strategies reported within the literature. Result in Table 1 show clearly that the proposed approach provides
higher results.
Table 1. Results of the minimum cost and power generation compared with:
SGA, EGA, IEP, FGA and MDE for IEEE 30-bus
Variables Our approach EPGA Global optimization methods
NP=1 NP=2 NP=3 SGA [19] EGA [3] IEP [20] FGA [21] MDE [11]
P1(MW) 180.12 175.12 174.63 179.367 176.20 176.2358 175.137 175.974
P2(MW) 44.18 48.18 47.70 44.24 48.75 49.0093 50.353 48.884
P5(MW) 19.64 20.12 21.64 24.61 21.44 21.5023 21.451 21.510
P8MW) 20.96 22.70 20.24 19.90 21.95 21.8115 21.176 22.240
P11(MW) 14.90 12.96 15.04 10.71 12.42 12.3387 12.667 12.251
P13(MW) 12.72 13.24 12.98 14.09 12.02 12.0129 12.11 12.000
Q1(Mvar) -4.50 -2.11 -2.03 -3.156 - - -6.562 -
Q2(Mvar) 30.71 32.57 32.42 42.543 - - 22.356 -
Q5(Mvar) 22.59 24.31 23.67 26.292 - - 30.372 -
Q8(Mvar) 37.85 27.82 28.22 22.768 - - 18.89 -
Q11(Mvar) -2.52 0.490 0.48 29.923 - - 21.737 -
Q13(Mvar) -13.08 -11.43 -11.43 32.346 - - 22.635 -
1(deg) 0.00 0.00 0.00 0.000 - - 0.00 -
2(deg) -3.448 -3.324 -3.313 -3.674 - - -3.608 -
5(deg) -9.858 -9.725 -9.623 -10.14 - - -10.509 -
8(deg) -7.638 -7.381 -7.421 -10.00 - - -8.154 -
11(deg) -7.507 -7.680 -7.322 -8.851 - - -8.783 -
13(deg) -9.102 -8.942 -8.926 -10.13 - - -10.228 -
Cost ($/hr) 801.34 800.83 800.92 803.699 802.06 802.465 802.0003 802.376
Ploss (MW) 9.120 8.920 8.833 9.5177 9.3900 9.494 9.459
CPU time(s) ~0.954 - - 594.08 - 23.07
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Table 1 denotes the cost consumption of the proposed and prevailing global methodologies.It is
clearly seen that the cost consumption of the prevailing methodologies such as Sga, tga,Iep,Fga and Mde.are
comparatively higher than that of the cost consumption of our proposed methodology implying EPGA.This
clearly depicts the cost efficiency of our framework from others.
Table 2 shows the best solution of shunt compensation obtained at the standard load demand
(Pd=283.4 MW) using reactive power planning. This describes the shunt reactive power compensation of
Epga and Ega where comparatively betterment is shown in favour of Epga. The transmission line loading
after optimization compared to aco and fga for ieee 30-bus as shown in Table 3.
Table 2. Comparative results of the shunt reactive power compensation between
EPGA and EGA [7] for ieee 30-bus
Shunt N° 1 2 3 4 6 7 8 9
Bus N° 10 12 15 17 21 23 24 29
Best Qsvc [pu] 0.1517 0.0781 0.029 0.0485 0.0602 0.0376 0.0448 0.0245
Best case bsh [pu] [7] 0.05 0.05 0.03 0.05 0.05 0.04 0.05 0.03
Table 3. Transmission line loading after optimization compared to ACO and FGA for ieee 30-bus
EPGA: PD=283.4 MW ACO [22] FGA [21]
Line Rating
(MVA)
From Bus
P(MW)
To Bus
P(MW)
To Bus
P(MW)
To Bus
+(P(MW))
1-2 130 113.9200 -7.7300 -119.5488 117.211
1-3 130 60.7100 5.7000 -58.3682 58.3995
2-4 65 32.0600 4.3000 -34.2334 34.0758
3-4 130 56.8600 3.7900 -55.5742 54.5622
2-5 130 62.4200 4.9000 -62.4522 63.7783
2-6 65 43.3000 2.4400 -44.5805 45.3399
4-6 90 49.1700 -8.0100 -49.0123 50.2703
5-7 70 -11.7900 7.2300 11.2939 14.1355
6-7 130 34.9800 0.8800 -34.0939 33.9924
6-8 32 11.8500 -1.3200 -11.0638 13.6882
6-9 65 16.5700 -3.3400 -19.7631 22.4033
6-10 32 12.5400 0.0700 -13.1277 14.6187
9-11 65 -15.0400 -0.0700 10.4330 24.1764
9-10 65 31.6100 -3.8000 -30.1961 32.7929
4-12 65 31.2200 16.7200 -33.1670 30.5889
12-13 65 -12.9800 11.8000 12.1730 24.9376
12-14 32 7.6600 1.0500 -8.0453 7.6911
12-15 32 18.1000 1.4900 -18.1566 17.4525
12-16 32 7.2400 1.3600 -7.4961 6.34027
14-15 16 1.4000 -0.6800 -1.8340 1.2313
16-17 16 3.6900 -0.5400 -3.9715 3.2983
15-18 16 5.8900 1.9700 -6.2224 5.4066
18-19 16 2.6500 1.0000 -3.0140 2.3627
19-20 32 -6.8500 -2.4100 6.5015 8.5117
10-20 32 9.1500 3.3200 -8.7015 11.0315
10-17 32 5.3200 0.8600 -5.0285 9.861616
10-21 32 16.1000 3.9800 -15.8419 18.96153
10-22 32 7.7800 1.7400 -7.6778 9.0741
21-22 32 -1.4800 -0.6100 1.6585 2.0887
15-23 16 5.2100 -0.7000 -5.4613 4.5343
22-24 16 6.2600 1.0400 -5.9593 6.9397
23-24 16 1.9900 1.8800 -2.2388 1.14447
24-25 16 -0.5000 1.1200 0.5027 1.3934
25-26 16 3.5400 2.3600 -3.5000 4.2647
25-27 16 -4.0500 -1.2400 4.0748 5.633
27-28 65 17.3200 2.9500 -17.3814 19.7428
27-29 16 6.1900 -0.2900 -6.1070 6.4154
27-30 16 7.0600 0.8900 -6.9295 7.2897
29-30 16 3.7200 1.3500 -3.6705 3.7542
8-28 32 2.0700 -2.1900 -2.2067 3.3685
6-28 32 15.2900 -0.6800 -15.1747 16.5409
Ploss (MW) 8.8836 9.8520 9.494
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The operation costs of the most effective solutions for the new system composed by 2 partitions and
for the new system composed by 3 partitions area unit 800.8336 $/h and 800.9265, severally , (0.0929
difference). The variations between the values are not important compared to the initial network while not
partitioning. This proves that the new subsystems generated conserve the physical proprieties and
performances of the initial network. Table three shows that the road flows obtained area unit well underneath
security limits compared to FGA algorithm and ACO algorithm [28].
4.1.2. Comparison with PSAT and MATPOWER OPF solver
For the purpose of verifying the robustness of the proposed algorithm we made a second comparison
with PSAT and MATPOWER packages under severe loading conditions. In this work the increase in the load
is regarded as a parameter which affects the power system to voltage collapse.
oL
L
oL
L
Q
Kld
Q
P
Kld
P
.
.
(23)
Where, oL
P and oL
Q are the active and reactive base loads, L
P and L
Q are the active and reactive
loads at bus L for the current operating point. Kld Represents the loading factor.
Table 4. Results of the minimum cost and power generation compared with:
PSAT and MATPOWER package for ieee 30-bus
Variables Our Approach EPGA MATPOWER PSAT
Kld=18% Kld=32% Kld=18% Kld=32% Kld=18% Kld=32%
P1(MW) 192.66 199.30 200.00 200.0 200.00 200.0
P2(MW) 58.94 70.60 55.00 69.74 54.9925 69.9368
P5(MW) 23.22 29.08 23.70 28.40 23.6957 28.5135
P8(MW) 33.98 33.66 35.00 35.00 35.00 35.00
P11(MW) 16.60 29.32 17.01 28.03 17.0154 28.2596
P13(MW) 20.40 25.10 15.84 26.47 15.8827 26.7635
Q1(Mvar) -5.26 -6.18 -13.94 -17.66 -15.6226 -9.4127
Q2(Mvar) 38.07 40.02 37.18 43.69 38.5416 60.4752
Q5(Mvar) 35.25 42.28 36.10 42.62 36.5254 49.5412
Q8(Mvar) 35.95 43.54 47.96 60.00 49.525 50.00
Q11(Mvar) 1.150 2.06 3.680 6.910 4.6425 21.1631
Q13(Mvar) -11.73 -11.04 -11.68 -2.270 2.3642 19.7389
1(deg) 0.00 0.00 0.00 0.00 0.00 0.00
2(deg) -3.684 -3.972 -4.028 -4.022 -4.0412 -4.026
5(deg) -11.218 -12.002 -11.841 -12.518 -11.8475 -12.6009
8(deg) -8.055 -8.588 -8.737 -9.065 -8.7607 -8.7792
11(deg) -11.995 -6.847 8.931 -7.386 -8.9022 -7.0128
13(deg) -9.344 -9.423 -10.642 -9.751 -10.6419 -9.8547
Cost ($/hr) 993.6802 1159.6 993.98 1160.56 994.1047 1164.1706
Ploss MW 11.390 12.975 12.141 13.556 12.174 14.385
The results together with the generation cost, the ability losses, reactive power generation, and also
the angles are shown in Table 4. We can clearly observe that the whole cost of generation and power losses
are higher than the results obtained by PSAT and MATPOWER at each loading issue (kld=18% and
kld=32%). as an example, at loading issue 32nd (PD=374.088) the distinction in generation cost between our
approach and to the 2 Packages (1159.6 $/h compared to 1160.56 $/h and 1164.1706 $/h) and in real power
loss (12.975 MW compared to thirteen.556 MW and 14.385 MW) obtained from MATPOWER and
PSAT severally.
Table 5 depicts the results of minimum cost, power generation, power losses, reactive power
generation, and angles. At loading issue kld=48.5%, the two simulation Package (PSAT and
MATPOWER) did not converge. A wider comparison is done with the PSAT and MATPOWER in order to
verify the robustness of this framework. Similarly, the cost factor also analyzed for betterment with both
methods. The approach proposed provides acceptable answer, the minimum total cost is 1403.5 $/h.
Voltage profile at loading factor: kld=48.5% as shown in Figure 5. Lines power flow at critical
loading factor kld= 48.5% as shown in Figure 6. Reactive power exchanged between SVC controllers and the
network at loading factor: kld=48.5% as shown ini Figure 7.
12. Int J Pow Elec & Dri Syst ISSN: 2088-8694
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Table 5. Results of the minimum cost and power generation compared with PSAT And MATPOWER
package for ieee 30-bus
Variables Loading Factor Kld=48.5%
PD=420.85 MW
Our Approach PSAT MATPOWER
P1(MW) 199.98
Did not Converge Did not Converge
P2(MW) 79.96
P5(MW) 49.98
P8(MW) 34.92
P11(MW) 30.00
P13(MW) 39.90
Q1(Mvar) -5.680
Q2(Mvar) 41.62
Q5(Mvar) 45.14
Q8(Mvar) 53.31
Q11(Mvar) 2.910
Q13(Mvar) -10.33
1(deg) 0.000
2(deg) -3.761
5(deg) -11.907
8(deg) -8.972
11(deg) -7.228
13(deg) -8.237
Cost ($/hr) 1403.5
Ploss (MW) 13.8960
Figure 5. Voltage profile at loading factor:
kld=48.5%
Figure 6. Lines power flow at critical loading factor
kld= 48.5%
Figure 7. Reactive power exchanged between SVC controllers and the network at loading factor:
kld=48.5%
0 5 10 15 20 25 30
0.95
1
1.05
1.1
Bus Number
V
olatage
Magnitude
Loading Factor kld=48.5%
PD=420.85 MW
0 10 20 30 40
-150
-100
-50
0
50
100
150
Lines Number
Line
P
ow
er
Flow
Rating Level(+)
Pji
Pij
Rating Level(-)
PD=420.85 MW
Loading Factor =48.5%
1 2 3 4 5 6 7 8
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
Bus Number
Reactive
Power
Exchanged
(SVC)
SVC at Bus 12
SVC at Bus 15
SVC at Bus 17
SVC at Bus 21
SVC at Bus 23
SVC at Bus 24
SVC at Bus 10
SVC at Bus 29
Loading Factor =48.5%
PD=420.85 MW
SVC Max =0.35 p.u
SVC Min =-0.35 p.u
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Figure 8. Convergence of IEEE 30 bus system
The protection constraints are checked for voltage magnitudes, angles and branch flows. The
protection constraints are checked for voltage magnitudes, angles and branch flows. Figure 5 shows that the
voltages magnitudes are within the desired security limits. Fig. 6 shows clearly that the transmission lines
loading do not exceed their higher limits. Figure 7 shows the reactive power changed between SVC
Controllers installed in at a specified buses and also the network.
The convergence values of IEEE 30 bus system on multi objective basis is shown in above Figure 8.
The variation with real power loss, reactive power loss, voltage profile and fuel cost for the standard IEEE 30
bus system with combined APO with AMO and APO is presented and it shows the importance of utilizing
APO with AMO than APO.
4.2. Case study 2 on IEEE 26-Bus test system with non-smooth cost function
This case study comprises of 6 generation units, 26 buses and 46 transmission lines [29] and all the
thermal units are within the ramp rate limits and prohibited zones. The data for this system is taken from the
reference [29], [30] and the load demand required for this system taken as PD=1263. The transmission loss
coefficient of the B matrix is determined as follows.
0
.
15
2
.
0
8
.
0
6
.
0
1
.
0
2
.
0
2
.
0
9
.
12
6
.
0
6
.
0
6
.
0
5
.
0
8
.
0
6
.
0
24
.
0
0
.
0
1
.
0
1
.
0
6
.
0
0
.
1
0
.
0
1
.
3
9
.
0
7
.
0
1
.
0
6
.
0
1
.
0
9
.
0
4
.
1
2
.
1
2
.
0
5
.
0
1
.
0
7
.
0
2
.
1
7
.
1
.
10 3
ij
B
(24)
6635
.
0
2161
.
0
0591
.
0
7047
.
0
1297
.
0
3908
.
0
.
10 3
0
i
B (25)
056
.
0
00
B (26)
Table 6 shows the performance comparison among the proposed algorithms, a particle swarm
optimization (PSO) approach [29], a novel string based GA [12], standard genetic algorithm (GA) method
[29], multiple task search algorithm (MTS) [13], and the simulated annealing (SA) method [13]. The
simulation results of the proposed approach outperformed recent optimization methods presented in the
14. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Solution for optimal power flow problem in wind energy system using hybrid... (P. Nagaleshmi)
499
literature in terms of solution quality and time convergence. The computational time of the proposed
approach is reduced significantly in comparison to the other methods.
Table 6. Results of the minimum cost and power generation compared with
global optimùization methods for 26-bus test system
Generators
(MW)
SA [13] New-string
GA [12]
GA [23] MTS [13] PSO [23] Our Approach
Pg1 Part1 478.1258 446.7100 474.8066 448.1277 447.4970 448.0451
Pg2 163.0249 173.0100 178.6363 172.8082 173.3221 172.0835
Pg3 Part2 261.7143 265.0000 262.2089 262.5932 263.4745 264.5932
Pg4 125.7665 139.0000 134.2826 136.9605 139.0594 134.9605
Pg5 Part3 153.7056 165.2300 151.9039 168.2031 165.4761 170.2452
Pg6 90.7965 86.7800 74.1812 87.3304 87.1280 85.2884
Total PG 1276.1339 1275.73 1276.03 1276.0232 1276.01 1275.20
Ploss (MW) 13.1317 12.733 13.0217 13.0205 12.9584 12.2160
Cost[$/hr] 15461.10 15447.00 15459.00 15450.06 15450.00 15439
CPU time(s) - 8.36 - 1.29 14.89 1.4380
4.3. Case study 3 on the IEEE 118-Bus
To investigate the strength of the projected approach the algorithmic program was enforced and
tested to the quality IEEE 118-bus model system (54 generators, 186 (line + transformer) and ninety nine
loads). The system load is 4242 MW and base MVA is 100 MVA. During this model, there are 54 generators
and that they are consists of various 18 characteristic generators [25]. The projected approach is compared to
the $64000 Genetic algorithmic program projected in [25]. The results pictured in Table 6 show clearly that
the projected approach provides far better results than the other technique. The distinction in generation value
between these 2 studies (6347.2$/h compared to 8278.9$/h) and in real power loss (106.788 MW compared
to 94.305 MW).
Figure 9. Topology of the IEEE 118-bus test system
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500
The optimum active powers ars bushed their secure limits values and are off from the physical
constraints limits. The protection constraints also are checked for voltage magnitudes and angles. Reactive
power designing [11], [12] applied within the second step based mostly in sensible fuzzy rules. Figure 9
show the topology the quality IEEE 118-Bus. Figure 10 shows that the reactive power generations are on
their security limits; Figure 11 shows the reactive power changed between the SVC Compensators put in at
crucial buses and also the network. Figure 12 demonstrates that the voltage profiles for all buses are
increased based mostly in reactive power designing sub problem.
The convergence values of IEEE 118 bus system on multi objective basis is shown in above
Figure 13. The variation with real power loss, reactive power loss, voltage profile and fuel cost for the
standard IEEE 30 bus system with combined APO with AMO and APO is presented and it shows the
importance of utilizing APO with AMO than APO.
The comparison Results of proposed method with GA for IEEE 118-Bus in terms of the Minimum
Cost and Power Generation is shown in Table 7.
Figure 10. Reactive power generation of IEEE 118-
bus electrical network with shunt compensation
(pd=4242 mw)
Figure 11. Reactive power compensation based
SVC compensators exchanged with the IEEE 118-
bus electrical network (pd=4242 mw)
Figure 12. Voltage profiles of IEEE 118-bus electrical network
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
41
43
45
47
49
51
53
55 57 59 61 63 65
67
69
71
73
75
77
79
81
83
85
87
89
91
93
95
97
99
101
103
105
107
109
111
113
115
117
Vmax Vmin
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501
Figure 13. Convergence of IEEE 118 bus system
Table 7. Results of the minimum cost and power generation compared with GA for IEEE 118-bus
Gen Type EPGA GA [19] Gen Type EPGA GA [19]
1
4
6
8
10
12
15
18
19
24
25
26
27
31
32
34
36
40
42
46
49
54
55
56
59
61
62
#1
#1
#1
#1
#2
#3
#1
#1
#1
#1
#4
#5
#1
#6
#1
#1
#1
#1
#1
#7
#8
#9
#1
#1
#10
#10
#1
10.840
11.280
16.840
21.380
258.86
92.760
10.000
10.000
10.780
10.060
289.98
411.80
13.700
43.100
11.020
12.160
10.300
14.180
15.100
73.420
101.24
40.820
13.140
14.520
157.26
41.920
11.820
11.99 33.603
10.191
10.038
162.09 63.06
28.439
10.398
10.023
13.178
282.02
376.55
29.683
67.232
14.144
12.912
12.639
66.505
19.805
13.345
217.88 52.24
14.431
23.335
59.497
195.11
43.015
65
66
69
70
72
73
74
76
77
80
85
87
89
90
91
92
99
100
103
104
105
107
110
111
112
113
116
#11
#11
#12
#1
#1
#1
#1
#1
#1
#13
#1
#14
#15
#1
#1
#1
#1
#16
#17
#1
#1
#1
#1
#18
#1
#1
#1
402.60
120.06
523.05
26.700
21.940
14.040
25.480
28.020
15.820
370.54
47.260
27.400
392.38
10.000
10.000
10.000
10.000
312.88
82.840
10.000
10.000
40.820
18.620
56.280
12.060
11.340
10.380
456.61
134.99
316.59
24.148
31.967
43.362
10.149 16.45
12.131
445.55
18.717
44.402
322.79
20.24
21.206
19.163
10.161
318.47
47.058
39.387
18.515
10.248
10.554
28.67
10.833
22.311
28.272
Cost($/hr)t 6347.2 8278.9
Losses (MW) 106.788 94.305
The comparison Results of proposed method with GA for IEEE 118-Bus in terms of the Minimum
Cost and Power Generation is shown in Table 7. Thus the cost factor for EPGA is given by 6347.2 and Power
generated is given by 106.788 MW which is seen that far better than compared with the GA whose minimum
cost is about 8278.9 which is comparatively higher than our proposed workwhich indicates our work as cost
effective one and similarly generated power is of 94.305 which is far much lesser than the framework.
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4.4. Result conclusion
It is clearly shown that the results obtained from our framework implying Epga has better results.
Initially, the comparison is done with Sga, Ega, Iep, Fga and Mde for justifying the. Obtained results. Similarly, in
order to verify the robustness, the proposed work is compared with Psat, Matpower.Then a brief comparison is
done with GA for justifying the betterment of process. Also, it is made damn clear, that from the above
figures and comparisons the clear knowledge and enhancement of process and importance of our proposed
method. The simulation results show that the multi objective problem is solved efficiently by using our
proposed APO with AMO algorithms than the existing methods. These make us to conclude that the
proposed research work will be a better of choice to solve optimal power flow problem with multi
objective function.
5. CONCLUSION
This article has conferred a unique HMOAPO algorithm and also the AMO algorithm to resolve the
OPF problem in electrical power systems. These algorithms are not to optimize multi objective functions at
the same time underneath the system constraints. The simulation results have verified the high performance
of each algorithms for resolution the target operate strategy within the customary IEEE 30-bus system.
Moreover, the DE algorithmic rule is employed to resolve multi-objective OPF issues with the assistance of
the fuzzy-based Pareto front methodology. It will be completed that the proposed APO algorithm-based
simulation results are competitive thereto of different recent optimization techniques. For an intensive
verification, each algorithms area unit applied to an outsized facility, i.e., the quality IEEE 118-bus system.
The simulation results have supported relevancy, potential, and effectiveness of those algorithms.
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