The purpose of distributed generation systems (DGS) is to enhance the distribution system (DS) performance to be better known with its benefits in the power sector as installing distributed generation (DG) units into the DS can introduce economic, environmental and technical benefits. Those benefits can be obtained if the DG units' site and size is properly determined. The aim of this paper is studying and reviewing the effect of connecting DG units in the DS on transmission efficiency, reactive power loss and voltage deviation in addition to the economical point of view and considering the interest and inflation rate. Whale optimization algorithm (WOA) is introduced to find the best solution to the distributed generation penetration problem in the DS. The result of WOA is compared with the genetic algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer (GWO). The proposed solutions methodologies have been tested using MATLAB software on IEEE 33 standard bus system
Coyote multi-objective optimization algorithm for optimal location and sizing...IJECEIAES
Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.
A hybrid algorithm for voltage stability enhancement of distribution systems IJECEIAES
This paper presents a hybrid algorithm by applying a hybrid firefly and particle swarm optimization algorithm (HFPSO) to determine the optimal sizing of distributed generation (DG) and distribution static compensator (D-STATCOM) device. A multi-objective function is employed to enhance the voltage stability, voltage profile, and minimize the total power loss of the radial distribution system (RDS). Firstly, the voltage stability index (VSI) is applied to locate the optimal location of DG and D-STATCOM respectively. Secondly, to overcome the sup-optimal operation of existing algorithms, the HFPSO algorithm is utilized to determine the optimal size of both DG and D-STATCOM. Verification of the proposed algorithm has achieved on the standard IEEE 33-bus and Iraqi 65-bus radial distribution systems through simulation using MATLAB. Comprehensive simulation results of four different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms in supporting voltage stability and loss reduction in distribution networks. Furthermore, comparisons have achieved to demonstrate the superiority of HFPSO algorithms over other techniques due to its ability to determine the global optimum solution by easy way and speed converge feature.
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.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
Minimization of real power loss and improvement of voltage authenticity of
the network are amongst the key issues confronting power systems owing to
the heavy demand development problem, contingency of transmission and
distribution lines and the financial costs. The distributed generators (DG) has
become one of the strongest mitigating strategies for the network power loss
and to optimize voltage reliability over integration of capacitor banks and
network reconfiguration. This paper introduces an approach for the
optimizing the placement and sizes of different types of DGs in radial
distribution systems using a fine-tuned particle swarm optimization (PSO).
The suggested approach is evaluated on IEEE 33, IEEE 69 and a real
network in Malaysian context. Simulation results demonstrate the
productiveness of active and reactive power injection into the electric power
system and the comparison depicts that the suggested fine-tuned PSO
methodology could accomplish a significant reduction in network power loss
than the other research works.
Grid reactive voltage regulation and cost optimization for electric vehicle p...nooriasukmaningtyas
Expecting large electric vehicle (EV) usage in the future due to environmental issues, state subsidies, and incentives, the impact of EV charging on the power grid is required to be closely analyzed and studied for power quality, stability, and planning of infrastructure. When a large number of energy storage batteries are connected to the grid as a capacitive load the power factor of the power grid is inevitably reduced, causing power losses and voltage instability. In this work large-scale 18K EV charging model is implemented on IEEE 33 network. Optimization methods are described to search for the location of nodes that are affected most due to EV charging in terms of power losses and voltage instability of the network. Followed by optimized reactive power injection magnitude and time duration of reactive power at the identified nodes. It is shown that power losses are reduced and voltage stability is improved in the grid, which also complements the reduction in EV charging cost. The result will be useful for EV charging stations infrastructure planning, grid stabilization, and reducing EV charging costs.
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
Optimal planning of RDGs in electrical distribution networks using hybrid SAP...IJECEIAES
The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA and PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA and PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
Coyote multi-objective optimization algorithm for optimal location and sizing...IJECEIAES
Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.
A hybrid algorithm for voltage stability enhancement of distribution systems IJECEIAES
This paper presents a hybrid algorithm by applying a hybrid firefly and particle swarm optimization algorithm (HFPSO) to determine the optimal sizing of distributed generation (DG) and distribution static compensator (D-STATCOM) device. A multi-objective function is employed to enhance the voltage stability, voltage profile, and minimize the total power loss of the radial distribution system (RDS). Firstly, the voltage stability index (VSI) is applied to locate the optimal location of DG and D-STATCOM respectively. Secondly, to overcome the sup-optimal operation of existing algorithms, the HFPSO algorithm is utilized to determine the optimal size of both DG and D-STATCOM. Verification of the proposed algorithm has achieved on the standard IEEE 33-bus and Iraqi 65-bus radial distribution systems through simulation using MATLAB. Comprehensive simulation results of four different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms in supporting voltage stability and loss reduction in distribution networks. Furthermore, comparisons have achieved to demonstrate the superiority of HFPSO algorithms over other techniques due to its ability to determine the global optimum solution by easy way and speed converge feature.
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.
Network loss reduction and voltage improvement by optimal placement and sizin...nooriasukmaningtyas
Minimization of real power loss and improvement of voltage authenticity of
the network are amongst the key issues confronting power systems owing to
the heavy demand development problem, contingency of transmission and
distribution lines and the financial costs. The distributed generators (DG) has
become one of the strongest mitigating strategies for the network power loss
and to optimize voltage reliability over integration of capacitor banks and
network reconfiguration. This paper introduces an approach for the
optimizing the placement and sizes of different types of DGs in radial
distribution systems using a fine-tuned particle swarm optimization (PSO).
The suggested approach is evaluated on IEEE 33, IEEE 69 and a real
network in Malaysian context. Simulation results demonstrate the
productiveness of active and reactive power injection into the electric power
system and the comparison depicts that the suggested fine-tuned PSO
methodology could accomplish a significant reduction in network power loss
than the other research works.
Grid reactive voltage regulation and cost optimization for electric vehicle p...nooriasukmaningtyas
Expecting large electric vehicle (EV) usage in the future due to environmental issues, state subsidies, and incentives, the impact of EV charging on the power grid is required to be closely analyzed and studied for power quality, stability, and planning of infrastructure. When a large number of energy storage batteries are connected to the grid as a capacitive load the power factor of the power grid is inevitably reduced, causing power losses and voltage instability. In this work large-scale 18K EV charging model is implemented on IEEE 33 network. Optimization methods are described to search for the location of nodes that are affected most due to EV charging in terms of power losses and voltage instability of the network. Followed by optimized reactive power injection magnitude and time duration of reactive power at the identified nodes. It is shown that power losses are reduced and voltage stability is improved in the grid, which also complements the reduction in EV charging cost. The result will be useful for EV charging stations infrastructure planning, grid stabilization, and reducing EV charging costs.
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
Optimal planning of RDGs in electrical distribution networks using hybrid SAP...IJECEIAES
The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA and PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA and PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.
Multi-objective optimal placement of distributed generations for dynamic loadsIJECEIAES
Large amount of active power losses and low voltage profile are the two major issues concerning the integration of distributed generations with existing power system networks. High R/X ratio and long distance of radial network further aggravates the issues. Optimal placement of distributed generators can address these issues significantly by alleviating active power losses and ameliorating voltage profile in a cost effective manner. In this research, multi-objective optimal placement problem is decomposed into minimization of total active power losses, maximization of bus voltage profile enhancement and minimization of total generation cost of a power system network for static and dynamic load characteristics. Optimum utilization factor for installed generators and available loads is scaled by the analysis of yearly load-demand curve of a network. The developed algorithm of N-bus system is implemented in IEEE-14 bus standard test system to demonstrate the efficacy of the proposed method in different loading conditions.
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.
Distribution network reconfiguration for loss reduction using PSO method IJECEIAES
In recent years, the reconfiguration of the distribution network has been proclaimed as a method for realizing power savings, with virtually zero cost. The current trend is to design distribution networks with a mesh network structure, but to operate them radially. This is achieved by the establishment of an appropriate number of switchable branches which allow the realization of a radial configuration capable of supplying all of the normal defects in the box of permanent defect. The purpose of this article is to find an optimal reconfiguration using a Meta heuristic method, namely the particle swarm optimization method (PSO), to reduce active losses and voltage deviations by taking into account certain technical constraints. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
Dual technique of reconfiguration and capacitor placement for distribution sy...IJECEIAES
Radial Distribution System (RDS) suffer from high real power losses and lower bus voltages. Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) techniques are ones of the most economic and efficient approaches for loss reduction and voltage profile improvement while satisfy RDS constraints. The advantages of these two approaches can be concentrated using of both techniques together. In this study two techniques are used in different ways. First, the DSR technique is applied individually. Second, the dual technique has been adopted of DSR followed by OCP in order to identify the technique that provides the most effective performance. Three optimization algorithms have been used to obtain the optimal design in individual and dual technique. Two IEEE case studies (33bus, and 69 bus) used to check the effectiveness of proposed approaches. A Direct Backward Forward Sweep Method (DBFSM) has been used in order to calculate the total losses and voltage of each bus. Results show the capability of the proposed dual technique using Modified Biogeography Based Optimization (MBBO) algorithm to find the optimal solution for significant loss reduction and voltage profile enhancement. In addition, comparisons with literature works done to show the superiority of proposed algorithms in both techniques.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
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.
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.
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 distributed generation in green building assessment towards line loss...journalBEEI
This paper presents an optimization approach for criteria setting of Renewable Distributed Generation (DG) in the Green Building Rating System (GBRS). In this study, the total line loss reduction is analyzed and set as the main objective function in the optimization process which then a reassessment of existing criteria setting for renewable energy (RE) is proposed towards lower loss outcome. Solar photovoltaic (PV)-type DG unit (PV-DG) is identified as the type of DG used in this paper. The proposed PV-DG optimization will improve the sustainable energy performance of the green building by total line losses reduction within accepted lower losses region using Artificial bee colony (ABC) algorithm. The distribution network uses bus and line data setup from selected one of each three levels of Malaysian public hospital. MATLAB simulation result shows that the PV-DG expanding capacity towards optimal scale and location provides a better outcome in minimizing total line losses within an appropriate voltage profile as compared to the current setting of PV-DG imposed in selected GBRS. Thus, reassessment of RE parameter setting and the proposed five rankings with new PV-DG setting for public hospital provides technical justification and give the best option to the green building developer for more
effective RE integration.
Critical Review of Different Methods for Siting and Sizing Distributed-genera...TELKOMNIKA JOURNAL
Due to several benefits attached to distributed generators such as reduction in line losses,
improved voltage profile, reliable system etc., the study on how to optimally site and size distributed
generators has been on the increase for more than two decades. This has propelled several
researchers to explore various scientific and engineering powerful simulation tools, valid and reliable
scientific methods like analytical, meta-heuristic and hybrid methods to optimally place and size
distributed generator(s) for optimal benefits. This study gives a critical review of different methods
used in siting and sizing distributed generators alongside their results, test systems and gaps in
literature.
Dynamic model of A DC-DC quasi-Z-source converter (q-ZSC)IJECEIAES
Two quasi-Z-source DC-DC converters (q-ZSCs) with buck-boost converter gain were recently proposed. The converters have advantages of continuous gain curve, higher gain magnitude and buck-boost operation at efficient duty ratio range when compared with existing q-ZSCs. Accurate dynamic models of these converters are needed for global and detailed overview by understanding their operation limits and effects of components sizes. A dynamic model of one of these converters is proposed here by first deriving the gain equation, state equations and state space model. A generalized small signal model was also derived before localizing it to this topology. The transfer functions (TF) were all derived, the poles and zeros analyzed with the boundaries for stable operations presented and discussed. Some of the findings include existence of right-hand plane (RHP) zero in the duty ratio to output capacitor voltage TF. This is common to the Z-source and quasi-Z-source topologies and implies control limitations. Parasitic resistances of the capacitors and inductors affect the nature and positions of the poles and zeros. It was also found and verified that rather than symmetric components, use of carefully selected smaller asymmetric components L1 and C1 produces less parasitic voltage drop, higher output voltage and current under the same conditions, thus better efficiency and performance at reduced cost, size and weight.
ASSESSMENT OF INTRICATE DG PLANNING WITH PRACTICAL LOAD MODELS BY USING PSO ecij
This paper presents the optimal sizing and placement of DG by assuming practical load models. The particle swarm optimization technique is used to minimize the multi-objective fitness function (MOFF). This MOFF has considered the performance indices such as a voltage difference index, active power loss index and reactive power loss index. Most of the studies have considered the constant load for distribution system planning which may mislead the exact assessment of the system performance. Thus the voltage dependency of load models is found in a highly demanding issue in updating researches. Keeping in view the urgent need of precise and flawless distribution system planning the effect of different load models on the total load, voltage profile, active and reactive power loss has been evaluated and presented in this paper. The efficacy of the proposed method has been executed by implementing it on the 33-bus radial test system.
An automated transmitter positioning system for misalignment compensation of...IJECEIAES
Misalignments are one of the most unfavorable aspects of the capacitive power transfer (CPT) system, which is inevitable in most of the applications. Misalignments affect the overall resonances in the circuit and decrease the power transfer capability and efficiency. In this paper, an automated electro-mechanical transmitter positioning system is proposed for capacitive wireless charging to withstand both axial and rotational misalignments. The system can align the transmitter based on an adaptive algorithm, with respect to the position of the receiver to mitigate the misalignments. The overall system is designed using SolidWorks and the algorithm is verified using Processing. Then, a hardware prototype is constructed in the laboratory. The accuracy of the proposed system is calculated and compared with the simulation results. The system can achieve an accuracy of 99.5%, in case of axial misalignment and an average accuracy of 98.6%, in case of both axial and rotational misalignments, which validate the 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.
Development of depth map from stereo images using sum of absolute differences...nooriasukmaningtyas
This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Model predictive controller for a retrofitted heat exchanger temperature cont...nooriasukmaningtyas
This paper aims to demonstrate the practical aspects of process control theory for undergraduate students at the Department of Chemical Engineering at the University of Bahrain. Both, the ubiquitous proportional integral derivative (PID) as well as model predictive control (MPC) and their auxiliaries were designed and implemented in a real-time framework. The latter was realized through retrofitting an existing plate-and-frame heat exchanger unit that has been operated using an analog PID temperature controller. The upgraded control system consists of a personal computer (PC), low-cost signal conditioning circuit, national instruments USB 6008 data acquisition card, and LabVIEW software. LabVIEW control design and simulation modules were used to design and implement the PID and MPC controllers. The performance of the designed controllers was evaluated while controlling the outlet temperature of the retrofitted plate-and-frame heat exchanger. The distinguished feature of the MPC controller in handling input and output constraints was perceived in real-time. From a pedagogical point of view, realizing the theory of process control through practical implementation was substantial in enhancing the student’s learning and the instructor’s teaching experience.
More Related Content
Similar to Energy harvesting maximization by integration of distributed generation based on economic benefits
Multi-objective optimal placement of distributed generations for dynamic loadsIJECEIAES
Large amount of active power losses and low voltage profile are the two major issues concerning the integration of distributed generations with existing power system networks. High R/X ratio and long distance of radial network further aggravates the issues. Optimal placement of distributed generators can address these issues significantly by alleviating active power losses and ameliorating voltage profile in a cost effective manner. In this research, multi-objective optimal placement problem is decomposed into minimization of total active power losses, maximization of bus voltage profile enhancement and minimization of total generation cost of a power system network for static and dynamic load characteristics. Optimum utilization factor for installed generators and available loads is scaled by the analysis of yearly load-demand curve of a network. The developed algorithm of N-bus system is implemented in IEEE-14 bus standard test system to demonstrate the efficacy of the proposed method in different loading conditions.
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.
Distribution network reconfiguration for loss reduction using PSO method IJECEIAES
In recent years, the reconfiguration of the distribution network has been proclaimed as a method for realizing power savings, with virtually zero cost. The current trend is to design distribution networks with a mesh network structure, but to operate them radially. This is achieved by the establishment of an appropriate number of switchable branches which allow the realization of a radial configuration capable of supplying all of the normal defects in the box of permanent defect. The purpose of this article is to find an optimal reconfiguration using a Meta heuristic method, namely the particle swarm optimization method (PSO), to reduce active losses and voltage deviations by taking into account certain technical constraints. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
Dual technique of reconfiguration and capacitor placement for distribution sy...IJECEIAES
Radial Distribution System (RDS) suffer from high real power losses and lower bus voltages. Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) techniques are ones of the most economic and efficient approaches for loss reduction and voltage profile improvement while satisfy RDS constraints. The advantages of these two approaches can be concentrated using of both techniques together. In this study two techniques are used in different ways. First, the DSR technique is applied individually. Second, the dual technique has been adopted of DSR followed by OCP in order to identify the technique that provides the most effective performance. Three optimization algorithms have been used to obtain the optimal design in individual and dual technique. Two IEEE case studies (33bus, and 69 bus) used to check the effectiveness of proposed approaches. A Direct Backward Forward Sweep Method (DBFSM) has been used in order to calculate the total losses and voltage of each bus. Results show the capability of the proposed dual technique using Modified Biogeography Based Optimization (MBBO) algorithm to find the optimal solution for significant loss reduction and voltage profile enhancement. In addition, comparisons with literature works done to show the superiority of proposed algorithms in both techniques.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
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.
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.
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 distributed generation in green building assessment towards line loss...journalBEEI
This paper presents an optimization approach for criteria setting of Renewable Distributed Generation (DG) in the Green Building Rating System (GBRS). In this study, the total line loss reduction is analyzed and set as the main objective function in the optimization process which then a reassessment of existing criteria setting for renewable energy (RE) is proposed towards lower loss outcome. Solar photovoltaic (PV)-type DG unit (PV-DG) is identified as the type of DG used in this paper. The proposed PV-DG optimization will improve the sustainable energy performance of the green building by total line losses reduction within accepted lower losses region using Artificial bee colony (ABC) algorithm. The distribution network uses bus and line data setup from selected one of each three levels of Malaysian public hospital. MATLAB simulation result shows that the PV-DG expanding capacity towards optimal scale and location provides a better outcome in minimizing total line losses within an appropriate voltage profile as compared to the current setting of PV-DG imposed in selected GBRS. Thus, reassessment of RE parameter setting and the proposed five rankings with new PV-DG setting for public hospital provides technical justification and give the best option to the green building developer for more
effective RE integration.
Critical Review of Different Methods for Siting and Sizing Distributed-genera...TELKOMNIKA JOURNAL
Due to several benefits attached to distributed generators such as reduction in line losses,
improved voltage profile, reliable system etc., the study on how to optimally site and size distributed
generators has been on the increase for more than two decades. This has propelled several
researchers to explore various scientific and engineering powerful simulation tools, valid and reliable
scientific methods like analytical, meta-heuristic and hybrid methods to optimally place and size
distributed generator(s) for optimal benefits. This study gives a critical review of different methods
used in siting and sizing distributed generators alongside their results, test systems and gaps in
literature.
Dynamic model of A DC-DC quasi-Z-source converter (q-ZSC)IJECEIAES
Two quasi-Z-source DC-DC converters (q-ZSCs) with buck-boost converter gain were recently proposed. The converters have advantages of continuous gain curve, higher gain magnitude and buck-boost operation at efficient duty ratio range when compared with existing q-ZSCs. Accurate dynamic models of these converters are needed for global and detailed overview by understanding their operation limits and effects of components sizes. A dynamic model of one of these converters is proposed here by first deriving the gain equation, state equations and state space model. A generalized small signal model was also derived before localizing it to this topology. The transfer functions (TF) were all derived, the poles and zeros analyzed with the boundaries for stable operations presented and discussed. Some of the findings include existence of right-hand plane (RHP) zero in the duty ratio to output capacitor voltage TF. This is common to the Z-source and quasi-Z-source topologies and implies control limitations. Parasitic resistances of the capacitors and inductors affect the nature and positions of the poles and zeros. It was also found and verified that rather than symmetric components, use of carefully selected smaller asymmetric components L1 and C1 produces less parasitic voltage drop, higher output voltage and current under the same conditions, thus better efficiency and performance at reduced cost, size and weight.
ASSESSMENT OF INTRICATE DG PLANNING WITH PRACTICAL LOAD MODELS BY USING PSO ecij
This paper presents the optimal sizing and placement of DG by assuming practical load models. The particle swarm optimization technique is used to minimize the multi-objective fitness function (MOFF). This MOFF has considered the performance indices such as a voltage difference index, active power loss index and reactive power loss index. Most of the studies have considered the constant load for distribution system planning which may mislead the exact assessment of the system performance. Thus the voltage dependency of load models is found in a highly demanding issue in updating researches. Keeping in view the urgent need of precise and flawless distribution system planning the effect of different load models on the total load, voltage profile, active and reactive power loss has been evaluated and presented in this paper. The efficacy of the proposed method has been executed by implementing it on the 33-bus radial test system.
An automated transmitter positioning system for misalignment compensation of...IJECEIAES
Misalignments are one of the most unfavorable aspects of the capacitive power transfer (CPT) system, which is inevitable in most of the applications. Misalignments affect the overall resonances in the circuit and decrease the power transfer capability and efficiency. In this paper, an automated electro-mechanical transmitter positioning system is proposed for capacitive wireless charging to withstand both axial and rotational misalignments. The system can align the transmitter based on an adaptive algorithm, with respect to the position of the receiver to mitigate the misalignments. The overall system is designed using SolidWorks and the algorithm is verified using Processing. Then, a hardware prototype is constructed in the laboratory. The accuracy of the proposed system is calculated and compared with the simulation results. The system can achieve an accuracy of 99.5%, in case of axial misalignment and an average accuracy of 98.6%, in case of both axial and rotational misalignments, which validate the 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.
Development of depth map from stereo images using sum of absolute differences...nooriasukmaningtyas
This article proposes a framework for the depth map reconstruction using stereo images. Fundamentally, this map provides an important information which commonly used in essential applications such as autonomous vehicle navigation, drone’s navigation and 3D surface reconstruction. To develop an accurate depth map, the framework must be robust against the challenging regions of low texture, plain color and repetitive pattern on the input stereo image. The development of this map requires several stages which starts with matching cost calculation, cost aggregation, optimization and refinement stage. Hence, this work develops a framework with sum of absolute difference (SAD) and the combination of two edge preserving filters to increase the robustness against the challenging regions. The SAD convolves using block matching technique to increase the efficiency of matching process on the low texture and plain color regions. Moreover, two edge preserving filters will increase the accuracy on the repetitive pattern region. The results show that the proposed method is accurate and capable to work with the challenging regions. The results are provided by the Middlebury standard dataset. The framework is also efficiently and can be applied on the 3D surface reconstruction. Moreover, this work is greatly competitive with previously available methods.
Model predictive controller for a retrofitted heat exchanger temperature cont...nooriasukmaningtyas
This paper aims to demonstrate the practical aspects of process control theory for undergraduate students at the Department of Chemical Engineering at the University of Bahrain. Both, the ubiquitous proportional integral derivative (PID) as well as model predictive control (MPC) and their auxiliaries were designed and implemented in a real-time framework. The latter was realized through retrofitting an existing plate-and-frame heat exchanger unit that has been operated using an analog PID temperature controller. The upgraded control system consists of a personal computer (PC), low-cost signal conditioning circuit, national instruments USB 6008 data acquisition card, and LabVIEW software. LabVIEW control design and simulation modules were used to design and implement the PID and MPC controllers. The performance of the designed controllers was evaluated while controlling the outlet temperature of the retrofitted plate-and-frame heat exchanger. The distinguished feature of the MPC controller in handling input and output constraints was perceived in real-time. From a pedagogical point of view, realizing the theory of process control through practical implementation was substantial in enhancing the student’s learning and the instructor’s teaching experience.
Control of a servo-hydraulic system utilizing an extended wavelet functional ...nooriasukmaningtyas
Servo-hydraulic systems have been extensively employed in various industrial applications. However, these systems are characterized by their highly complex and nonlinear dynamics, which complicates the control design stage of such systems. In this paper, an extended wavelet functional link neural network (EWFLNN) is proposed to control the displacement response of the servo-hydraulic system. To optimize the controller's parameters, a recently developed optimization technique, which is called the modified sine cosine algorithm (M-SCA), is exploited as the training method. The proposed controller has achieved remarkable results in terms of tracking two different displacement signals and handling external disturbances. From a comparative study, the proposed EWFLNN controller has attained the best control precision compared with those of other controllers, namely, a proportional-integralderivative (PID) controller, an artificial neural network (ANN) controller, a wavelet neural network (WNN) controller, and the original wavelet functional link neural network (WFLNN) controller. Moreover, compared to the genetic algorithm (GA) and the original sine cosine algorithm (SCA), the M-SCA has shown better optimization results in finding the optimal values of the controller's parameters.
Decentralised optimal deployment of mobile underwater sensors for covering la...nooriasukmaningtyas
This paper presents the problem of sensing coverage of layers of the ocean in three dimensional underwater environments. We propose distributed control laws to drive mobile underwater sensors to optimally cover a given confined layer of the ocean. By applying this algorithm at first the mobile underwater sensors adjust their depth to the specified depth. Then, they make a triangular grid across a given area. Afterwards, they randomly move to spread across the given grid. These control laws only rely on local information also they are easily implemented and computationally effective as they use some easy consensus rules. The feature of exchanging information just among neighbouring mobile sensors keeps the information exchange minimum in the whole networks and makes this algorithm practicable option for undersea. The efficiency of the presented control laws is confirmed via mathematical proof and numerical simulations.
Evaluation quality of service for internet of things based on fuzzy logic: a ...nooriasukmaningtyas
The development of the internet of thing (IoT) technology has become a major concern in sustainability of quality of service (SQoS) in terms of efficiency, measurement, and evaluation of services, such as our smart home case study. Based on several ambiguous linguistic and standard criteria, this article deals with quality of service (QoS). We used fuzzy logic to select the most appropriate and efficient services. For this reason, we have introduced a new paradigmatic approach to assess QoS. In this regard, to measure SQoS, linguistic terms were collected for identification of ambiguous criteria. This paper collects the results of other work to compare the traditional assessment methods and techniques in IoT. It has been proven that the comparison that traditional valuation methods and techniques could not effectively deal with these metrics. Therefore, fuzzy logic is a worthy method to provide a good measure of QoS with ambiguous linguistic and criteria. The proposed model addresses with constantly being improved, all the main axes of the QoS for a smart home. The results obtained also indicate that the model with its fuzzy performance importance index (FPII) has efficiently evaluate the multiple services of SQoS.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Smart monitoring system using NodeMCU for maintenance of production machinesnooriasukmaningtyas
Maintenance is an activity that helps to reduce risk, increase productivity, improve quality, and minimize production costs. The necessity for maintenance actions will increase efficiency and enhance the safety and quality of products and processes. On getting these conditions, it is necessary to implement a monitoring system used to observe machines' conditions from time to time, especially the machine parts that often experience problems. This paper presents a low-cost intelligent monitoring system using NodeMCU to continuously monitor machine conditions and provide warnings in the case of machine failure. Not only does it provide alerts, but this monitoring system also generates historical data on machine conditions to the Google Cloud (Google Sheet), includes which machines were down, downtime, issues occurred, repairs made, and technician handling. The results obtained are machine operators do not need to lose a relatively long time to call the technician. Likewise, the technicians assisted in carrying out machine maintenance activities and online reports so that errors that often occur due to human error do not happen again. The system succeeded in reducing the technician-calling time and maintenance workreporting time up to 50%. The availability of online and real-time maintenance historical data will support further maintenance strategy.
Design and simulation of a software defined networkingenabled smart switch, f...nooriasukmaningtyas
Using sustainable energy is the future of our planet earth, this became not only economically efficient but also a necessity for the preservation of life on earth. Because of such necessity, smart grids became a very important issue to be researched. Many literatures discussed this topic and with the development of internet of things (IoT) and smart sensors, smart grids are developed even further. On the other hand, software defined networking is a technology that separates the control plane from the data plan of the network. It centralizes the management and the orchestration of the network tasks by using a network controller. The network controller is the heart of the SDN-enabled network, and it can control other networking devices using software defined networking (SDN) protocols such as OpenFlow. A smart switching mechanism called (SDN-smgrid-sw) for the smart grid will be modeled and controlled using SDN. We modeled the environment that interact with the sensors, for the sun and the wind elements. The Algorithm is modeled and programmed for smart efficient power sharing that is managed centrally and monitored using SDN controller. Also, all if the smart grid elements (power sources) are connected to the IP network using IoT protocols.
Efficient wireless power transmission to remote the sensor in restenosis coro...nooriasukmaningtyas
In this study, the researchers have proposed an alternative technique for designing an asymmetric 4 coil-resonance coupling module based on the series-to-parallel topology at 27 MHz industrial scientific medical (ISM) band to avoid the tissue damage, for the constant monitoring of the in-stent restenosis coronary artery. This design consisted of 2 components, i.e., the external part that included 3 planar coils that were placed outside the body and an internal helical coil (stent) that was implanted into the coronary artery in the human tissue. This technique considered the output power and the transfer efficiency of the overall system, coil geometry like the number of coils per turn, and coil size. The results indicated that this design showed an 82% efficiency in the air if the transmission distance was maintained as 20 mm, which allowed the wireless power supply system to monitor the pressure within the coronary artery when the implanted load resistance was 400 Ω.
Topology network effects for double synchronized switch harvesting circuit on...nooriasukmaningtyas
Energy extraction takes place using several different technologies, depending on the type of energy and how it is used. The objective of this paper is to study topology influence for a smart network based on piezoelectric materials using the double synchronized switch harvesting (DSSH). In this work, has been presented network topology for circuit DSSH (DSSH Standard, Independent DSSH, DSSH in parallel, mono DSSH, and DSSH in series). Using simulation-based on a structure with embedded piezoelectric system harvesters, then compare different topology of circuit DSSH for knowledge is how to connect the circuit DSSH together and how to implement accurately this circuit strategy for maximizing the total output power. The network topology DSSH extracted power a technique allows again up to in terms of maximal power output compared with network topology standard extracted at the resonant frequency. The simulation results show that by using the same input parameters the maximum efficiency for topology DSSH in parallel produces 120% more energy than topology DSSH-series. In addition, the energy harvesting by mono-DSSH is more than DSSH-series by 650% and it has exceeded DSSHind by 240%.
Improving the design of super-lift Luo converter using hybrid switching capac...nooriasukmaningtyas
In this article, an improvement to the positive output super-lift Luo converter (POSLC) has been proposed to get high gain at a low duty cycle. Also, reduce the stress on the switch and diodes, reduce the current through the inductors to reduce loss, and increase efficiency. Using a hybrid switch unit composed of four inductors and two capacitors it is replaced by the main inductor in the elementary circuit. It’s charged in parallel with the same input voltage and discharged in series. The output voltage is increased according to the number of components. The gain equation is modeled. The boundary condition between continuous conduction mode (CCM) and discontinuous conduction mode (DCM) has been derived. Passive components are designed to get high output voltage (8 times at D=0.5) and low ripple about (0.004). The circuit is simulated and analyzed using MATLAB/Simulink. Maximum power point tracker (MPPT) controls the converter to provide the most interest from solar energy.
Third harmonic current minimization using third harmonic blocking transformernooriasukmaningtyas
Zero sequence blocking transformers (ZSBTs) are used to suppress third harmonic currents in 3-phase systems. Three-phase systems where singlephase loading is present, there is every chance that the load is not balanced. If there is zero-sequence current due to unequal load current, then the ZSBT will impose high impedance and the supply voltage at the load end will be varied which is not desired. This paper presents Third harmonic blocking transformer (THBT) which suppresses only higher harmonic zero sequences. The constructional features using all windings in single-core and construction using three single-phase transformers explained. The paper discusses the constructional features, full details of circuit usage, design considerations, and simulation results for different supply and load conditions. A comparison of THBT with ZSBT is made with simulation results by considering four different cases
Power quality improvement of distribution systems asymmetry caused by power d...nooriasukmaningtyas
With an increase of non-linear load in today’s electrical power systems, the rate of power quality drops and the voltage source and frequency deteriorate if not properly compensated with an appropriate device. Filters are most common techniques that employed to overcome this problem and improving power quality. In this paper an improved optimization technique of filter applies to the power system is based on a particle swarm optimization with using artificial neural network technique applied to the unified power flow quality conditioner (PSO-ANN UPQC). Design particle swarm optimization and artificial neural network together result in a very high performance of flexible AC transmission lines (FACTs) controller and it implements to the system to compensate all types of power quality disturbances. This technique is very powerful for minimization of total harmonic distortion of source voltages and currents as a limit permitted by IEEE-519. The work creates a power system model in MATLAB/Simulink program to investigate our proposed optimization technique for improving control circuit of filters. The work also has measured all power quality disturbances of the electrical arc furnace of steel factory and suggests this technique of filter to improve the power quality.
Studies enhancement of transient stability by single machine infinite bus sys...nooriasukmaningtyas
Maintaining network synchronization is important to customer service. Low fluctuations cause voltage instability, non-synchronization in the power system or the problems in the electrical system disturbances, harmonics current and voltages inflation and contraction voltage. Proper tunning of the parameters of stabilizer is prime for validation of stabilizer. To overcome instability issues and get reinforcement found a lot of the techniques are developed to overcome instability problems and improve performance of power system. Genetic algorithm was applied to optimize parameters and suppress oscillation. The simulation of the robust composite capacitance system of an infinite single-machine bus was studied using MATLAB was used for optimization purpose. The critical time is an indication of the maximum possible time during which the error can pass in the system to obtain stability through the simulation. The effectiveness improvement has been shown in the system
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
Intelligent fault diagnosis for power distribution systemcomparative studiesnooriasukmaningtyas
Short circuit is one of the most popular types of permanent fault in power distribution system. Thus, fast and accuracy diagnosis of short circuit failure is very important so that the power system works more effectively. In this paper, a newly enhanced support vector machine (SVM) classifier has been investigated to identify ten short-circuit fault types, including single line-toground faults (XG, YG, ZG), line-to-line faults (XY, XZ, YZ), double lineto-ground faults (XYG, XZG, YZG) and three-line faults (XYZ). The performance of this enhanced SVM model has been improved by using three different versions of particle swarm optimization (PSO), namely: classical PSO (C-PSO), time varying acceleration coefficients PSO (T-PSO) and constriction factor PSO (K-PSO). Further, utilizing pseudo-random binary sequence (PRBS)-based time domain reflectometry (TDR) method allows to obtain a reliable dataset for SVM classifier. The experimental results performed on a two-branch distribution line show the most optimal variant of PSO for short fault diagnosis.
A deep learning approach based on stochastic gradient descent and least absol...nooriasukmaningtyas
More than eighty-five to ninety percentage of the diabetic patients are affected with diabetic retinopathy (DR) which is an eye disorder that leads to blindness. The computational techniques can support to detect the DR by using the retinal images. However, it is hard to measure the DR with the raw retinal image. This paper proposes an effective method for identification of DR from the retinal images. In this research work, initially the Weiner filter is used for preprocessing the raw retinal image. Then the preprocessed image is segmented using fuzzy c-mean technique. Then from the segmented image, the features are extracted using grey level co-occurrence matrix (GLCM). After extracting the fundus image, the feature selection is performed stochastic gradient descent, and least absolute shrinkage and selection operator (LASSO) for accurate identification during the classification process. Then the inception v3-convolutional neural network (IV3-CNN) model is used in the classification process to classify the image as DR image or non-DR image. By applying the proposed method, the classification performance of IV3-CNN model in identifying DR is studied. Using the proposed method, the DR is identified with the accuracy of about 95%, and the processed retinal image is identified as mild DR.
Automated breast cancer detection system from breast mammogram using deep neu...nooriasukmaningtyas
All over the world breast cancer is a major disease which mostly affects the women and it may also cause death if it is not diagnosed in its early stage. But nowadays, several screening methods like magnetic resonance imaging (MRI), ultrasound imaging, thermography and mammography are available to detect the breast cancer. In this article mammography images are used to detect the breast cancer. In mammography image the cancerous lumps/microcalcifications are seen to be tiny with low contrast therefore it is difficult for the doctors/radiologist to detect it. Hence, to help the doctors/radiologist a novel system based on deep neural network is introduced in this article that detects the cancerous lumps/microcalcifications automatically from the mammogram images. The system acquires the mammographic images from the mammographic image analysis society (MIAS) data set. After pre-processing these images by 2D median image filter, cancerous features are extracted from the images by the hybridization of convolutional neural network with rat swarm optimization algorithm. Finally, the breast cancer patients are classified by integrating random forest with arithmetic optimization algorithm. This system identifies the breast cancer patients accurately and its performance is relatively high compared to other approaches.
Max stable set problem to found the initial centroids in clustering problemnooriasukmaningtyas
In this paper, we propose a new approach to solve the document-clustering using the K-Means algorithm. The latter is sensitive to the random selection of the k cluster centroids in the initialization phase. To evaluate the quality of K-Means clustering we propose to model the text document clustering problem as the max stable set problem (MSSP) and use continuous Hopfield network to solve the MSSP problem to have initial centroids. The idea is inspired by the fact that MSSP and clustering share the same principle, MSSP consists to find the largest set of nodes completely disconnected in a graph, and in clustering, all objects are divided into disjoint clusters. Simulation results demonstrate that the proposed K-Means improved by MSSP (KM_MSSP) is efficient of large data sets, is much optimized in terms of time, and provides better quality of clustering than other methods.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
About
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.
• 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.
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.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...
Energy harvesting maximization by integration of distributed generation based on economic benefits
1. Indonesian Journal of Electrical Engineering and Computer Science
Vol. 25, No. 2, February 2022, pp. 610~625
ISSN: 2502-4752, DOI: 10.11591/ijeecs.v25.i2.pp610-625 610
Journal homepage: http://ijeecs.iaescore.com
Energy harvesting maximization by integration of distributed
generation based on economic benefits
Tarek A. Boghdady1
, Samar G. A. Nasser2
, Essam El-Din Aboul Zahab1
1
Department of Electrical power Engineering, Faculty of Engineering, Cairo university, Giza, Egypt
2
Department of Electrical Power Engineering, Institute of Aviation Engineering and Technology (I.A.E.T), Giza, Egypt
Article Info ABSTRACT
Article history:
Received Jan 27, 2021
Revised Dec 19, 2021
Accepted Dec 27, 2021
The purpose of distributed generation systems (DGS) is to enhance the
distribution system (DS) performance to be better known with its benefits in
the power sector as installing distributed generation (DG) units into the DS
can introduce economic, environmental and technical benefits. Those
benefits can be obtained if the DG units' site and size is properly determined.
The aim of this paper is studying and reviewing the effect of connecting DG
units in the DS on transmission efficiency, reactive power loss and voltage
deviation in addition to the economical point of view and considering the
interest and inflation rate. Whale optimization algorithm (WOA) is
introduced to find the best solution to the distributed generation penetration
problem in the DS. The result of WOA is compared with the genetic
algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer
(GWO). The proposed solutions methodologies have been tested using
MATLAB software on IEEE 33 standard bus system.
Keywords:
Distributed generation
Genetic algorithm
Grey wolf optimizer
Particle swarm optimization
Whale optimization algorithm
This is an open access article under the CC BY-SA license.
Corresponding Author:
Tarek A. Boghdady
Department of Electrical Power Engineering, Faculty of Engineering, Cairo University
El Gamma Street, Giza, Egypt
Email: Engtarek82@gmail.com
1. INTRODUCTION
In the last few years, society and electric power system utilities have met numerous economic,
environmental and technical power quality problems associated with power systems. So, with better energy
planning and the use of emerging smart technology, research is now making a great effort to pay attention to
the existing infrastructure. One of the most applicable solutions for improving DS performance is the
optimum allocation of distributed generation (DG) in the distribution system (DS). As the non-optimal
allocation of DG may consequence in an increase in energy loss, lower voltage profile than acceptable
boundaries in addition to high expends [1]. If real active power losses are far higher than the normal values,
DS companies in Egypt are economically penalized. Or, on the other hand, they gain a good profit [2]. Also,
high real active power losses decrease the transmission efficiency to the end user; therefore, its decrease
attracted much more attention from distribution companies [3]. Likewise, decreasing the reactive power loss
is also objective that should be taken into consideration during DG planning. Thus, reducing the reactive
power consumption, diminishing voltage drops and empowering system loadability are one of the most
common objectives [4]. Moreover, it aids active power flow through transmission and distribution (T&D)
lines to the end user [3].
The optimal DG size and site supports in decreasing the resistance losses (𝐼2
𝑅), the reactance losses
(𝐼2
𝑥) and consequently the voltage drop in the two components (IR and IX) in the DS [2]. Many research
objectives in DG planning based on the single objective index (SOI) almost as if it were real power or
2. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
611
minimizing the energy loss of the DS and not taking note of the merits of the sum of the weighted multi-
objectives index (MOI), such as energy loss minimization, voltage profile enhancement and total cost
reduction of the DS. A new proposed optimization technique is proposed for location and how to size the DG
in DS with a changed loading conditions for minimization of real power loss of the system, is proposed
in [5]-[7]. The MOI of performance for DS with DG, which includes a wide range of electric technical
problems, is proposed in [8]. The optimal MOI sizing and location of multiple DGS in addition to shunt
capacitor banks all together in view of load uncertainty by adjusted particle swarm optimization (PSO)
approach from dissimilar power system performances views, is presented in [9].
A technique on empowering the power system parameters systems by selecting the optimally
located DG in DS is proposed in [10]. States that the effect that was elevated because of the joining of DG
into the present network from different power system performances viewpoints [11]. The objective function
contains voltage profile enhancement and power losses minimization using ant colony algorithm, the
suggested method was confirmed on IEEE 33-bus test system, the results display a significant lessening in
the total power loss and enhanced voltage profiles of all the buses. Correspondingly, allocating of DGS and
optimal penetration of solid state fault current limiters (SSFCLs) have been applied [12]-[13]. It was also
discovered that adding DG units to the DS decreases the reactive and active power loss and enhance the
stability of voltage of the system. PSO has been presented in [14] for penetration of DGS for loss
minimization. Several researches motivated in decreasing the system losses neglecting the costs of losses,
DGS units' connection and its maintenance. Although particular papers [15]-[18] they took these costs into
account, but only concentrated on improving voltage stability without reducing system losses. This paper is
providing a complete review on the effect of connecting DG units in the DS. Comprehensive methodology
using genetic algorithm is proposed and other methods to determine:
− Optimum size DGs and maximization SOI of transmission efficiency.
− Optimum site DGs and maximization SOI of transmission efficiency.
− Allocation of DGs and maximization SOI of transmission efficiency.
− Allocation of DGs and minimization MOI of reactive power loss (Qloss), voltage deviation (VD) and
maximization of transmission efficiency.
− Allocation of DGs and minimization SOI of total cost and maximization of transmission efficiency.
The proposed 33-bus IEEE DS radial algorithms were applied and the results were compared with
other techniques. The backward/forward sweep (BFS) method is used here for lateral radial DS power flow
analysis because it is simple to implement, flexible, fast, and has extreme accuracy [19]-[20]. The rest of this
paper is arranged as follows. Section 2 discusses the problem formulation, while sections 3 present
methodology and 4 present simulation results, finally the paper conclusions explained in section 5.
2. PROBLEM FORMULATION
2.1. Power flow formulation
The BFS algorithm for Figure 1 measures the power flow estimates. Shows the DS segment,
provided that the N line is linked between the two ‘i’ and ‘j’ buses given. Three measures based on the
currents and voltage law of the Kirchhoff are used to evaluate the BFS technique Kirchhoff's current law
(KCL) and Kirchhoff's voltage law (KVL), correspondingly. The three stages are: (a) backward sweep, (b)
forward sweep, and (c) nodal current analysis. Such measures depend on concourse achievements if the
maximum mismatch between voltages is less than the epsilon acceptance provided.
Figure 1. A section of DS
It is easy to estimate the active and reactive power losses for the radial DS after the concourse.
The BFS power flow evaluations are presented as: the flow of active (P_ij) and reactive (Q_ij) powers from
node ‘i’ to node ‘j’ via branch ‘N’ can be obtained from the latest node in (a) backwards sweep path as:
3. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
612
𝑃𝑖𝑗 = 𝑃𝑗
′
+ 𝑅𝑖𝑗
(𝑃𝑗
′2
+𝑄𝑗
′2
)
𝑉𝑗
2 (1)
𝑄𝑖𝑗 = 𝑄𝑗
′
+ 𝑋𝑖𝑗
(𝑃𝑗
′2
+𝑄𝑗
′2
)
𝑉𝑗
2 (2)
where, 𝑃𝑖𝑗
`
= 𝑃𝑗 + 𝑃𝐿𝑗 and 𝑄𝑖𝑗
`
= 𝑄𝑗 + 𝑄𝐿𝑗 . 𝑃𝐿𝑗 and 𝑄𝐿𝑗 are loads that are attached at node ‘j’. 𝑃𝑗 𝑎𝑛𝑑 𝑄𝑗
are the active and reactive power flowing from node ‘j’.
The magnitude and angle of voltage at each node are considered in (b) forward direction. take into
account a voltage 𝑉𝑖∠𝛿i at node ‘i’ and 𝑉𝑗∠𝛿𝑗 at node ‘j’, then the (c) the current flowing through the branch
‘N’ having an impedance, 𝑍𝑖𝑗 = 𝑅𝑖𝑗 + 𝑗𝑋𝑖𝑗 linked between ‘I’ and ‘j’ are given as:
𝐼𝑖𝑗 =
(𝑉𝑗∠𝛿𝑗−𝑉𝑗∠𝛿𝑗 )
𝑅𝑖𝑗 + 𝑗𝑋𝑖𝑗
(3)
𝐼𝑖𝑗 =
(𝑃𝑖−𝑗𝑄𝑖)
𝑉𝑗∠−𝛿𝑗
(4)
hence from (3) and (4) the bus voltage at ‘j’ can be calculated as:
𝑉
𝑗 = [𝑉𝑖
2
− 2 ∗ (𝑃𝑖𝑅𝑖𝑗 + 𝑗𝑄𝑖𝑋𝑖𝑗) + (𝑅𝑖𝑗
2
+ 𝑋𝑖𝑗
2
) ∗
𝑃𝑖
2
+𝑄𝑖
2
𝑉𝑖
2 ]0.5 (5)
the magnitude and phase angle equations can be suggested correspondingly in (b) the forward direction to
find the voltage and angle of all radial DS nodes. It is possible to present the active and reactive power losses
of line ‘N’ between buses ‘i’ and ‘j’ as:
𝑃𝑙𝑜𝑠𝑠(𝑖𝑗) = 𝑅𝑖𝑗
(𝑃𝑖𝑗
2
+𝑄𝑖𝑗
2
)
𝑉𝑖
2 (6)
𝑄𝑙𝑜𝑠𝑠(𝑖𝑗) = 𝑋𝑖𝑗
(𝑃𝑖𝑗
2
+𝑄𝑖𝑗
2
)
𝑉𝑖
2 (7)
the total active power loss of radial DS can be considered as:
𝑃𝑇𝑙𝑜𝑠𝑠 = ∑ 𝑃𝑙𝑜𝑠𝑠(𝑖𝑗)
𝑁
𝑗=1 (8)
where ‘N’ is the number of branches, i=1: n and ‘n’ is the number of buses.
2.2. Power loss estimation in case of existing DGS units
Then the power losses within a line sector in Figure 1 when putting DG units in the DS. It is:
𝑃𝐷𝐺,𝑙𝑜𝑠𝑠(𝑖𝑗) = 𝑅𝑖𝑗
(𝑃𝐷𝐺(𝑖𝑗)
2
+𝑄𝐷𝐺(𝑖𝑗)
2
)
𝑉𝑖
2 (9)
𝑃𝐷𝐺,𝑇𝐿𝑂𝑆𝑆 = ∑ 𝑃𝐷𝐺,𝑙𝑜𝑠𝑠(𝑖𝑗)
𝑁
𝑗=1 (10)
where, 𝑃𝐷𝐺,𝑙𝑜𝑠𝑠(𝑖𝑗) and 𝑄𝐷𝐺,𝑙𝑜𝑠𝑠(𝑖𝑗)is the active and reactive power loss when locating DGS between buses ‘i’
and ‘j’, 𝑃𝐷𝐺,𝑇𝐿𝑂𝑆𝑆 is the total power loss with locating DGS.
2.3. Index of power losses
The total power loss index 𝛥𝑃𝑙𝐷𝐺 is calculated as the division of total power loss with connecting
DGS by the total power loss without connecting DGS and it is presented as:
∆𝑃𝑙𝐷𝐺 =
𝑃𝐷𝐺,𝑇𝐿𝑂𝑆𝑆
𝑃𝑇𝐿𝑂𝑆𝑆
(11)
by minimizing, the total power loss in the system reduced by integration DGS.
4. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
613
2.4. Voltage deviation index (VDI)
The VDI can be presented as (12).
𝑉𝐷 = max (
𝑉1−𝑉𝑖
𝑉1
), ∀ 𝑖 = 1,2, … … … . , 𝑛 (12)
2.5. DGS cost evaluation
DS companies are mainly responsible for providing the demand of end user. So that, benefits and
costs of DGs site and size in a utility network may be proposed as shown:
− Cost of investment
Investment cost includes DG units cost, investigation fee, DG units installation, preparation of location.
It can be presented as:
𝐶1 = ∑ 𝐾𝐷𝐺𝑖
𝑁𝐷𝐺
𝑖=1 ∗ 𝐼𝐶𝑖 (13)
where, i=1, 2, 3 … NDG, no. of DGS that should be located. K_DGi Is the MW capacity of i DG. IC_i
is the initial cost of i DG in $/MW.
− Cost of operation
DG operating cost is mainly depending on DGs operation to produce power for end users can be
presented as:
𝐶2 = ∑ [𝐾𝐷𝐺𝑖
𝑁𝐷𝐺
𝑖=1 ∗ 𝑂𝐶𝑖] ∗ ∆𝑇 (14)
while, OCi is the cost of operation of i DG in $/MWh of i DG , ∆T is the operating hours during a year.
And if the inflation rate (IF) and the interest rate (IR), so that the present worth value (PWV) can be
signified as:
𝛽𝑡
= ∑𝑛
𝑡=1 (
1+𝐼𝐹
1+𝐼𝑅
)𝑡
(15)
where, 𝛽𝑡
is PWV, n is the planning period in years. PWV of operating cost in planning year can be
considered as:
𝑃𝑊𝑉(𝐶2) = ∑ [𝐾𝐷𝐺𝑖
𝑁𝐷𝐺
𝑖=1 ∗ 𝑂𝐶𝑖] ∗ ∆𝑇 ∗ 𝛽𝑡
(16)
− Maintenance cost
MCDGi Can be calculated as (percentage% of initial cost per year.
2.6. DGS benefits evaluation
− Real power demand decreases from DS network
In an energy efficient power system, transmission grid sold its power to DS company to achieve the
energy request of end users. DS corporation can resource demand of power with existing of DGS, then
obtain lower electrical power from transmission grid. DS company can create a market and sell the
energy to the grid as per agreed contract as shown:
𝐵1 = ∑ 𝐾𝐷𝐺𝑖
𝑁𝐷𝐺
𝑖=1 ∗ 𝐸𝑃𝐺 ∗ ∆𝑇 (17)
while, EPG is the price of electricity in ($/KWh), and ∆T is time segment in which energy is sold to grid.
PWV of the generated electricity from DG by the DS company can be considered as shown:
𝑃𝑊𝑉(𝐵1) = ∑ 𝐾𝐷𝐺𝑖
𝑁𝐷𝐺
𝑖=1 ∗ 𝐸𝑃𝐺 ∗ ∆𝑇 ∗ 𝛽𝑡
(18)
− Loss reduction revenue
Economic benefit is the main target of DS company for maximizing the profit. So, the revenue came
from the loss reduction in the existence of DGs estimated as:
𝐵2 = ∑ ∆ 𝐿𝑂𝑆𝑆𝑖𝑗
𝑁𝐷𝐺
𝑖=1 ∗ 𝐸𝑃𝐺 ∗ ∆𝑇 (19)
∆ LOSSij Is the active power loss reduction, when DGs is sited in the network and EPG is the electricity
price in the grid in $/kWh. The PWV of loss reduction revenue in a planned zone can be calculated as:
5. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
614
𝑃𝑊𝑉(𝐵2) = ∑ ∆ 𝐿𝑂𝑆𝑆𝑖𝑗
𝑁𝐷𝐺
𝑖=1 ∗ 𝐸𝑃𝐺 ∗ ∆𝑇 ∗ 𝛽𝑡
(20)
3. METHODOLGY
It is commonly known that the MOF is mathematically modeled in order to optimize the obtained
benefits of the DG integration into the DS in terms of different indices. These indices importance appears
when planning and operation of DG because of their significant impact on the income of utilities', power
quality, security, environmental effect and system stability [4]. In our review we have two phases, the first
one was maximizing transmission efficiency, minimizing voltage deviation and reactive power loss. The
second phase was a single objective function (SOI) to minimize the total cost. The MOF can be stated as the
weighted sum of the transmission efficiency (TEI) and the voltage deviation index (VDI) and reactive power
loss reduction index (QLI). The weighted summation method is efficient, the development of a strongly non-
dominated solution that can be used as the initial solution for other approaches is simple and feasible [21].
MOF minimization can be stated from (21):
𝑀𝑖𝑛𝑖𝑚𝑖𝑧𝑒 (𝑀𝑂𝐹) = 𝑚𝑖𝑛 [𝑊𝑝𝑙𝑃𝐿𝐼 + 𝑊𝑄𝐿 𝑄𝐿𝐼 + 𝑊𝑉𝐷 𝑉𝐷𝐼] (21)
𝑊𝑝𝑙 + 𝑊𝑄𝐿 + 𝑊𝑉𝐷 = 1 (22)
the reactive power loss reduction (WQL), voltage deviation (WVD ). The transmission efficiency are each
assigned with different weighting factors according to their importance.
3.1. Reactive and real power loss indices (𝑸𝑳𝑰, PLI)
In this approach, the benefits can be achieved when lowering the indices values. The reactive and
real power loss indices are well-defined as;
𝑃𝐿𝐼 =
𝑃𝐿𝐷𝐺
𝑃𝐿
(23)
𝑄𝐿𝐼 =
𝑄𝐿𝐷𝐺
𝑄𝐿
(24)
where, QLDG and PLDG are the total reactive and real power losses of the DS after presence of DG. QL and
PL are the total reactive and real losses without existing DG in the DS.
3.2. Voltage deviation index (𝑽𝑫𝑰)
In this approach, the better network performance can be achieved when this index is much lower.
Selecting the proper location of DG improves the voltage profile. This index maybe is used for finding the
DG locations taking into consideration the pre-established voltage deviation limit, and also for ensuring the
rated voltage concerned for each bus within the allowable limits. Where, V1 is the rated voltage
(normallyV1=100%), ‘n’ is the nodes number and Vi is the bus I voltage. The VDI can be estimated:
𝑉𝐷𝐼 = 𝑚𝑎𝑥 (
𝑉1−𝑉𝑖
𝑉1
), ∀ 𝑖 = 1,2, … … … . , 𝑛 (25)
3.3. Maximizing profit (𝐌𝐏)
In a few words, the view point of benefit and cost that have been shown in the previous sections are
worked in a one single objective function (SOF) that is expressed below for maximizing the distribution
company profit taking into consideration the constraints.
max profit = 𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝑠 − Investments (26)
Min cost = ∑ KDGi
NDG
i=1 ∗ EPG ∗ ∆T ∗ βt
+ ∑ ∆losss ∗ EPG
NDG
i=1 − ∑ KDGi
NDG
i=1 ∗ OCi ∆T ∗ βt
−
∑ [KDGi
NDG
i=1 ∗ ICi ∗ {1MCDG ∗ βt
}] (27)
3.4. Solution methodology for multiple DG connecting
The methodology of connecting for multi DG can be expressed in three stages. The first stage is
identifying the optimal DG location, then the optimal DG size and finally by optimizing the optimal
placement and size.
6. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
615
3.4.1. Identifying the optimal DG source’s location
This procedure is repetitive for multiple DGs connecting. The starting base system is reformed by
considering a fixed optimal DG size at the best locations in the DS configuration (DSC) firstly by injecting a
DG unit one-by-one in the DSC. The obtained DG will be located in the system so that developing a new
staring base case with repetitive steps of placing single DG. The best select of DG sizes cannot be the optimal
overall choices. It is reasonably illustrated that the optimal DG (size and placement) is optimum choice at the
time of adding of each DG, but not for the overall complete system. However, the optimum overall global
DG size choices are detected by using algorithms provided that the placement of DGs which are strong-
minded by single algorithms of placing DGs.
3.4.2. Identifying the global optimal DG sources sizes
The common procedure for obtaining the optimal sizing of multi-DG connecting is as follows:
1) Input probable buses that are the best optimal DG locations are given by single placement of DG and
applying genetic algorithm again.
2) In a random way selecting the initial GA population.
3) Applying the power flow for the DSC with the existing of the injected DG at the best optimal location.
4) Assess the needed objective function by the power flow with the existing of the inserted DG from the
GA search.
5) Repeating steps 3, 4 for all groupings populations of GA.
6) Giving values to the objective function as a fitness to GA.
7) Checking the criteria of GA convergence if it's satisfied then goes to step no 9.
8) Generating one a new generation and then go to step no 3.
9) Printing the result for all probable candidate buses.
3.4.3. Optimal sites and sizes of DG using GA
This process is repetitive for multiple locations and sizes of DGs. By using GA, simply we can
obtain both the optimal site and size for the following cases:
a) Consider existing of 1 DG.
b) Consider existing of 2 DG.
c) Consider existing of 3 DG.
4. RESULTS AND DISCUSSION
The test system is the standard 33 bus radial DS network given in Figure 2(a) and Figure 2(b), with
number of thirty -two branches and three laterals. The reactive and real powers of the connected loads for this
network are 2.3 MVAR and3.72 MW respectively. The active and reactive power losses for this radial DS
network without DGs are 201.893 kW and 134.641 kVAR respectively.
(a) (b)
Figure 2. The test system is the standard 33 bus radial DS network: (a) single line diagram of standard IEEE
33 bus DS and (b) magnitude of the node voltage of base case of 33-bus test DS
4.1. Using single objective function of transmission efficiency
4.1.1. Optimum size DGs
Assuming DG location as follows:
a) Existing one DG at bus 6 as it is the longest branch and near to load center.
b) The results as shown in Table 1 are approximately equal between optimization techniques and the
optimal size is 2588 kw at bus 6.
c) Existing two DG at bus 6 and 18 as it is near to load center and the end node of the longest branch.
d) The results as shown in Table 1 show the optimal size to achieve maximum transmission is 2079 kw at
7. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
616
bus 6 and 462 kw at bus 18.
e) Existing 3DG at bus 6.18, and 33 near to load center, the end node of the longest branch, and second far
end node at the second-largest branch.
f) The results as shown in Table 1 are the optimum size, in this case, obtained by GWO or WOA is
1396 kw at bus 6, 457 kw at bus 18, and 658 kw at bus 33.
Before installing the DG, the voltage profiles of some of the buses in all distribution systems exceed
the required constraint limitations. As a result, after using the genetic algorithm to identify the ideal size DG
as the base technique, the voltage profile of all buses in all systems moved to the suitable range, as shown in
Figure 3(a). After adding DG sources, there is the increase in the system's transmission efficiency. Compared
to single DG placement, the total DG capacity mounted in the device is smaller for multi DG positioning
after putting the optimal DG determined by the genetic algorithm as base technique as shown in Figure 3(b).
Table 1. Global optimum size of DGs for transmission efficiency maximization
CASE
NO.
BASE W/O
DG (kw)
201.893
Techniques
GA PSO WOA GWO
1 DG BUS NO. - 6 6 6 6
DG SIZE (kw) - 2818 2588 2588 2588
Power Loss (kw) - 103.05.00 102.08.00 102.08.00 102.08.00
P LOSS reduction % - 48% 49% 49% 49%
2 DG BUS NO. - 6 18 6 18 6 18 6 18
DG SIZE (kw) - 2856 338 2079 462 2099 456 2099 456
Overall Size (kw) - 3194 2541 2555 2555
Power Loss (kw) - 97 90.08.00 90.08.00 90.08.00
P LOSS reduction % - 52% 55% 55.1% 55.1%
3 DG BUS NO. - 6 18 33 6 18 33 6 18 33 6 18 33
DG SIZE (kw) - 1804 250 617 1510 442 708 1383 459 663 1396 457 658
Overall Size (kw) - 2671 2660 2505 2511
Power Loss (kw) - 81.01.00 78.71 78.33.00 78.32.00
P LOSS reduction% - 59.8% 61% 61.2% 61.2%
(a) (b)
Figure 3. Optimum allocation of DGs: (a) magnitude of the node voltage and (b) transmission efficiency
4.1.2. Optimum site DGs
Assuming DG size from the results as follows in Table 1:
− Existing one DG with size 2588 kw.
− The results are witten in Table 2 are approximately equal between optimization techniques and the
optimal site is bus 6. The loss reduction percentage, in this case, is 49%.
− Existing two DG with size 2079 kw and 462 kw as in WOA.
− The results are shown in Table 2 illustrate the optimal site to achieve maximum transmission at bus 6
and bus 18. The loss reduction percentage, in this case, is 55.6%.
− Existing 3DG for example from different techniques with sizes 1510, 442, and 708 kw as in PSO.
− The results shown in Table 2 are the optimum site at bus 29, bus 16, and bus 25. The loss reduction
percentage, in this case, is 62.4%.
Before installing the DG, the voltage profiles of some buses in the distribution system exceed the
required constraint limitations. As a result, after using the different optimization algorithmes to identify the
optimum site DG for the three cases (1 DG, 2 DG, and 3 DG). The voltage profile of all buses in all systems
moved to the suitable range, as shown in Figure 4(a). There is the increase in the system's transmission
8. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
617
efficiency after adding DG sources, when compared to the base case without DG and the single DG
installation. After using the genetic algorithm to select the optimum DG site, as shown in Figure 4(b).
(a)
(b)
Figure 4. Optimum site of DGs: (a) magnitude of the node voltage and (b) transmission efficiency
Table 2. Global optimum site of DGs for transmission efficiency maximization
CASE
NO.
BASE W/O DG
(kw)
201.893
Techniques
GA PSO WOA GWO
IDG DG SIZE (kw) - 2818 2588 2588 2588
BUS NO. - 6 6 6 6
Power Loss (kw) - 103.05.00 102.08.00 102.08.00 102.08.00
P LOSS reduction
%
- 48% 49% 49% 49%
2DG DG SIZE (kw) - 2856 338 2079 462 2079 462 2079 462
BUS NO. - 6 16 26 15 6 15 7 15
Overall Size (kw) - 3194 3541 2541 2541
Power Loss (kw) - 96.07.00 89.07.00 89.06.00 91.02.00
P LOSS reduction
%
- 51.9% 55.5% 55.6% 54.8%
3DG DG SIZE (kw) - 1804 250 617 1510 442 708 459 663 1383 1396 457 658
BUS NO. - 6 17 31 29 16 25 14 25 30 7 15 31
Overall Size (kw) - 2671 2660 2505 2511
Power Loss (kw) - 80.34.00 75.94 75.34.00 76.05.00
P LOSS reduction
%
- 60.2% 62.4% 62.3% 62%
4.1.3. Optimum allocation of DGs
This section looks at the problem for one, two, and three DGs existing. The different techniques
determine the appropriate position of the DG unit, in addition to its size. But the previous sections determine
the size only or position of the units. The results of this section are summarized in Table 3. The voltage
profile of all buses is enhanced and is within the acceptable range in all three cases (after inserting the
optimum location and capacity of the one, two, and three DG units) as shown in Figure 5(a). It illustrates that
the better voltage profile, the greater the number of DG units. The increasing in the system's transmission
efficiency after adding DG sources is shown in Figure 5(b).
9. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
618
Table 3. Global Optimum allocation of DGs for transmission efficiency maximization
CASE
NO.
BASE W/O
DG (kw)
201.893
Techniques
GA PSO WOA GWO
I DG DG SIZE (kw) - 2588 2455 2588 2588
BUS NO. - 6 26 6 6
Power Loss
(KW)
- 102.08 104.03 102.08 102.08
P LOSS
reduction %
- 49% 48.3% 49% 49%
2DG DG SIZE (kw) - 1192 850 850 1192 850 1192 1000 1126
BUS NO. - 13 30 13 30 14 30 12 30
Overall Size
(kw)
- 2042 2042 2042 2126
Power Loss
(KW)
- 82.09 82.09.00 83 83.02.00
P LOSS
reduction %
- 59% 59% 58.9% 58.8%
3DG DG SIZE (kw) - 725 1070 1119 759 1071 1100 759 1071 1100 1383 1000 1000
BUS NO. - 14 24 30 14 24 30 15 24 31 3 12 30
Overall Size
(kw)
- 2914
293
0
2930 3383
Power Loss
(KW)
- 69.04 69.4 71.03 76.06
P LOSS
reduction %
-
65.6
%
56.6
%
64.8% 62%
(a)
(b)
Figure 5. Global optimum allocation of DGs: (a) magnitude of the node voltage and
(b) transmission efficiency
4.2. Optimum allocation of DGs and minimization of total cost as SOI
The total cost can be minimized by selecting the optimum allocation of DGs taking into
consideration the interest and inflation rate, thus we can extract the maximum profit, and certain assumptions
are considered. The effect of DG placement and capacity in a 33-bus test system was demonstrated in Table 4
as a result of the simulation. The price list of DG units from generator joe company, the cost of service and
maintenance are shown in Table 5, and the benefit earned during the planning period. For serval study
duration, optimum positioning and size are carried out with DG. Table 4 presents the financial and technical
benefits and profits of DG size and placement, based on the results of simulation by the proposed GA as base
algorithm compared with other techniques of algorithms, and presents the best Global optimal location and
size of DG sources for minimizing total cost in case of injecting three DGs with overall capacity 600 kw only
at bus bar (15, 18, 32), the profit 1.5508*10^6 $ and the loss reduction percentage 52.9% taking into
consideration interest and inflation rates. In the case of injecting two DGs with an overall capacity of 400
KW only at the bus bar (32, 17), the profit 0.92471*10^6 $ and the loss reduction percentage 23%. In the
10. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
619
case of injecting one DG with an overall capacity of 200 kw only at the bus bar (17), the profit 0.88717*10^6
$ and the loss reduction percentage 12.5%.
The voltage profile is shown in Figure 6(a) as an obtained by genetic algorithm and this is the worst
solution technique for optimum allocation of DGs for minimizing total cost as SOI. The values of voltage
profile at some buses in the non-acceptable range. The Transmission efficiency of this case is shown in
Figure 6(b). The transmission efficiency is not sufficiently improved like in previous cases, in addition to the
economic profit was higher because this is from the economic point of view.
Table 4. Global optimum allocation of DGs for minimizing total cost
CASE
NO.
BASE W/O DG
(kw)
201.893
Techniques
GA PSO WOA GWO
I DG DG SIZE (kw) - 200 200 200 200
BUS NO. - 33 17 17 17
Power Loss (KW) - 178.07 176.06 176.06 176.06
P LOSS reduction % - 11.5% 12.5% 12.5% 12.5%
Profit*10^6 - 0,613194444 0,615972222 0,615972222 0,615972222
2 DG DG SIZE (kw) - 200 200 200 200 200 200 200 200
BUS NO. - 17 15 17 32 17 33 32 17
Power Loss (KW) - 167.05 155.02 155.03 155.02
P LOSS reduction % - 17% 23.2% 23.1% 23.2%
Profit*10^6 0.90324 0.92471 0.92466 0.92471
3 DG DG SIZE (kw) - 200 200 200 200 200 200 200 200 200 200 200 200
BUS NO. - 7 20 29 14 17 32 15 18 32 14 17 32
Power Loss (KW) - 164.09 137.06 95.02 137.06
P LOSS reduction % - 18.3% 31.9% 52.9% 31.9%
Profit*10^6 - 14.294 14.770 15.508 14.770
(a)
(b)
Figure 6. Optimum allocation of DGs for minimizing total cost: (a) magnitude of the node voltage and
(b) transmission efficency
Table 5. The sample of price list of DG units from generator joe company
Diesel
generators
list price of
Generator
joe co,
Sets 60 HZ 200 KW 210 KW 250 KW 275 KW 280 KW 300 KW 350 KW 400 KW 450 KW
investment
cost ($)
46,705.6 51,823.6 53,673.9 57,902.5 54,310.7 61,708.1 65,791.3 68,253.2 76,978.8
fuel cost 5g/hr-
13.4
15.5 g/h 18.5 g/h 19.5 g/h 19.5 g/h 23 g/h 23 g/h 25.8 g/h 29.9 g/h
40.2$/h 46.5$/h 55.5 $/h 58.5 $/h 58.5$/h 69 $/h 69 $/h 77.4 $/h 89.7 $/h
4.2. Optimum allocation of DGs and minimization MOI of reactive power loss (Qloss), voltage
deviation (VD) and maximization of transmission efficiency
It is presented as a case study in the first and then changed the weights, which the reactive power
loss reduction, voltage deviation, and the transmission efficiency. Each index is assigned with different
weighting factors according to their importance to get the best global performance index:
11. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
620
a) Case study
From the utility point of view, is enhancing transmission efficiency to deliver energy to end-users
with high transmission efficiency and high power quality. So, assume the weight factors to be W1=0.5,
W2=0.25, and W3=0.25 from (21), (22). When changed the weights in this case study as according to some
ref [22]-[25] with optimum size and site of DGs for existence one, two, and three DGs, the results are
summarized in Table 6. The voltage profile of all buses is enhanced and is within the acceptable range in
three cases as shown in Figure 7(a). The transmission efficiency of optimum allocation of DGs for
minimizing MOI is shown in Figure 7(b).
Table 6. Global optimum allocation of DGs for minimizing MOI
CASE
NO.
BASE W/O
DG (kw)
201.893
Techniques
GA PSO WOA GWO
I DG BUS NO. - 6 6 6 6
DG SIZE
(kw)
- 2959 2952 2952 2952
Power Loss
(KW)
- 104.07 104.06 104.06 104.06
P LOSS
reduction%
- 48% 48.2% 48.2% 48.2%
2DG BUS NO. - 13 30 30 13 13 31 6 15
DG SIZE
(kw)
- 991 1203 1270 957 957 1270 2266 563
Overall Size
(kw)
- 2221 2227 2227 2829
Power Loss
(KW)
- 83.08 38.83 86.67 90.01
P LOSS
reduction %
- 58% 58.5% 57% 55.4%
3DG BUS NO. - 14 24 30 30 14 24 25 15 31 30 4 14
DG SIZE
(kw)
- 852 1066 1192 1113 794 1050 1084 852 1188 1070 1112 901
Overall Size
(kw)
- 3110 2957 3124 3083
Power Loss
(KW)
- 70.03 69.05 74.07 77.05
P LOSS
reduction %
- 65% 65.6% 63% 61.6%
(a)
(b)
Figure 7. Optimum allocation of DGs for minimizing MOI: (a) magnitude of the node voltage and
(b) transmission efficiency
b) Changing the weight factors by parito method to achieve the best MOI
− Allocation by (constant weight of transmission efficiency equal to 0.1) and changing other weights from
0.1 to 0.8 So that it is equal to 1. The best case that appeared when W1=0.1, W2=0.1, and W3=0.8,
12. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
621
when allocated DGs for minimizing MOI by using this weights factor. So, the voltages profile is
dominant. The end node voltage is improved and arrived at 1pu approximately because of the largest
weight comparing to another weight as shown in Figure 8(a). The transmission efficiency of optimum
allocation of DGs for minimizing MOI taking into consideration voltage profile is shown in Figure 8(b).
When changed the weights of this case study as according to the largest problem in the grid (VD) with
optimum size and site of DGs for existence one, two, and three DGs, the results are summarized in
Table 7.
(a)
(b)
Figure 8. Optimum allocation of DGs for minimizing MOI taking into consideration voltage profile:
(a) magnitude of the node voltage and (b) transmission efficiency
Table 7. Global optimum allocation of DGs sources for minimizing MOI taking into consideration
voltage profile
CASE
NO.
BASE W/O
DG (kw)
201.
893
Techniques
GA PSO WOA GWO
I DG BUS NO. - 6 6 6 26
DG SIZE
(kw)
- 4047 4222 4222 4061
Power Loss
(KW)
- 130.07 137.06 137.06 104.09
P LOSS
reduction %
- 35.3% 31.8% 31.8% 30.2%
2DG BUS NO. - 13 30 6 14 13 31 30 14
DG SIZE
(kw)
- 991 1203 1270 957 957 1270 2266
56
3
Overall Size
(kw)
- 2761 3683 2761 2772
Power Loss
(KW)
- 95.05 106.02 101.09 96.09
P LOSS
reduction %
- 52.7% 47.4% 49.5% 51.9%
3DG BUS NO. - 13 24 30 31 14 6 4 31 13 2 16 6
DG SIZE
(kw)
- 1079 1187 1481 962 824 1480 2061 1399 1030 3608 492
31
81
Overall Size
(kw)
- 3747 3266 4490 7281
Power Loss
(KW)
- 81.72 85.98 102.6 113
P LOSS
reduction %
- 59.5% 57.4% 49% 44%
− Allocation by (constant weight of reactive power loss equal to 0.1) and changing other weights from 0.1
to 0.8 so that it is equal to 1. The best case that appeared when W1=0.8, W2=0.1, and W3=0.1, When
13. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
622
made the penetration DG for minimizing MOI by using this weights factor. So, transmission efficiency
is dominant because of the largest weight comparing to another weight. When changed the weights of
this case as according to the largest problem (PL) in the grid with optimum size and site of DGs for
existence one, two, and three DGs, the results are summarized in Table 8. The voltage profile of all
buses is enhanced and is within the acceptable range in three cases as shown in Figure 9(a). The
transmission efficiency of optimum allocation of DGs for minimizing MOI is shown in Figure 9(b).
(a)
(b)
Figure 9. Optimum allocation of DGs for minimizing MOI taking into consideration maximizing
transmission efficiency: (a) magnitude of the node voltage and (b) transmission efficiency
Table 8. Global optimum allocation of DGs for minimizing MOI
CASE
NO.
BASE W/O
DG (kw)
201.893
Techniques
GA PSO WOA GWO
I DG BUS NO. - 6 6 6 6
DG SIZE
(kw)
- 2707 2723 2723 2723
Power Loss
(KW)
- 102.09 103 103 103
P LOSS
reduction %
- 49% 48.9% 48.9% 48.9%
2DG BUS NO. - 13 30 30 13 13 30 27 14
DG SIZE
(kw)
- 893 1222 1222 893 893 1222 1823 638
Overall
Size (kw)
- 2115 2115 2115 2461
Power Loss
(KW)
- 83.01.00 83.01 83.01 88.03
P LOSS
reduction %
- 58.9% 58.9% 58.9% 56.3%
3DG BUS NO. - 14 24 30 14 30 3 14 25 30 14 30 25
DG SIZE
(kw)
- 797 1000 1124 770 1083 1626 797 1075 1134 911 1071 464
Overall
Size (kw)
- 2921 3479 3006 2446
Power Loss
(KW)
- 69.52 75.06 70.85 73.03
P LOSS
reduction %
- 65.6% 62.8% 64.9% 63.7%
− Allocation by (Constant weight of voltage deviation equal to 0.1) and changing other weights from 0.1
to 0.8 so that it is equal to 1. The best case that appeared when W1=0.1, W2=0.8, and W3=0.1, When
made the penetration DG for minimizing MOI by using this weights factor. So, reactive power loss is
the dominant because of the largest weight comparing to other weights. The voltage profile of all buses
is enhanced and is within the acceptable range in three cases as shown in Figure 10(a). The transmission
14. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
623
efficiency of optimum allocation of DGs for minimizing MOI is shown in Figure 10(b). When changed
the weights of this case as according to the largest problem (QL) in the grid with optimum size and site
of DGs for existence one, two, and three DGs, the results are summarized in Table 9.
Table 9. Global optimum allocation of DGs for minimizing MOI taking into consideration reactive power
CASE
NO.
BASE W/O
DG (kw)
201.89
3
Techniques
GA PSO WOA GWO
I DG BUS NO. - 6 6 6 6
DG SIZE (kw) - 2710 2676 2676 2675
Power Loss
(KW)
- 102.09 102.08 102.08 102.08
P LOSS
reduction %
- 48.9% 49% 49% 49%
2DG BUS NO. - 13 30 30 13 13 30 6 3
DG SIZE (kw) - 991 1170 1070 900 900 1170 2469 1627
Overall Size
(kw)
- 2070 1970 2070 4096
Power Loss
(KW)
- 82.09 38.03 82.09 100.09
P LOSS
reduction %
- 58.9% 58.7% 58.9% 50%
3DG BUS NO. - 13 24 30 13 30 24 32 7 15 12 3 6
DG SIZE (kw) - 852 1041 1090 852 1090 1041 730 1128 666 1222 915 1233
Overall Size
(kw)
- 2983 2983 2524 3370
Power Loss
(KW)
- 69.65 69.65 76.35 92.96
P LOSS
reduction %
- 65.5% 65.5%
62.2
%
53.9%
(a)
(b)
Figure 10. Optimum placement and size for minimizing MOI taking into consideration reactive power:
(a) magnitude of the node voltage and (b) transmission efficiency
5. CONCLUSION
This paper has introduced an intensive review for obtaining the optimal DG Site, Size and
Penetration between them for single and multiple DGs to fulfill economic, environmental and technical
benefits using single and Multi objective indices based on a comparison between the best performance
existed by GA, PSO, GWO, and WOP algorithms. The proposed algorithm techniques were tested on 33-bus
radial DS and the results can be summarized as presented.
By Allocating DG units at the optimal location the system loadability is enhanced. The voltage
profile is enhanced at all nodes in which DG units are best located while compared to the case that no
15. ISSN: 2502-4752
Indonesian J Elec Eng & Comp Sci, Vol. 25, No. 2, February 2022: 610-625
624
allocation for DG units. While increasing the DGs penetration level, at a Particular point the increasing in
reduction of losses is not much noticeable when compared to the cost increase due to this highly penetration
level. The GWO has presented the best Global optimal location and size of DG sources for minimizing total
cost in case of injecting three DGs taking into consideration interest and inflation rates.
REFERENCES
[1] M. M. Aman, G. B. Jasmon, A. H. A. Bakar, and H. Mokhlis, “Optimum network reconfiguration based on maximization of
system loadability using continuation power flow theorem,” International journal of electrical power & energy systems, vol. 54,
pp. 123-133, 2014, doi: 10.1016/j.ijepes.2013.06.026.
[2] S. Kalambe, and G. Agnihotri, “Loss minimization techniques used in distribution network: bibliographical survey,” Renewable
and sustainable energy reviews, vol. 29, pp. 184-200, 2014, doi: 10.1016/j.rser.2013.08.075.
[3] L. Ramesh, S. P. Chowdhury, S. Chowdhury, Y. H. Song, and A. A. Natarajan, “Voltage stability analysis and real power loss
reduction in distributed distribution system,” In 2008 IEEE/PES Transmission and Distribution Conference and Exposition, 2008,
pp. 1-6, doi: 10.1109/TDC.2008.4517070.
[4] D. Q. Hung, and N. Mithulananthan, “Loss reduction and loadability enhancement with DG: A dual-index analytical approach,”
Applied energy, vol. 115, pp. 233-241, 2014, doi: 10.1016/j.apenergy.2013.11.010.
[5] D. Singh, D. Singh, and K. S. Verma, “GA based energy loss minimization approach for optimal sizing & placement of
distributed generation,” International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 12, no. 2,
pp. 147-156, 2008, doi: 10.3233/KES-2008-12206.
[6] D. A. Amon, “A modified bat algorithm for power loss reduction in electrical distribution system,” Indonesian Journal of
Electrical Engineering and Computer Science (IJEECS), vol. 14, no. 1, pp. 55-61, 2015, doi: 10.11591/telkomnika.v14i1.7629.
[7] A. A. J. Jeman, N. M. S. Hannoon, N. Hidayat, M. M. H. Adam, I. Musirin, and V. Vijayakumar, “Active and reactive power
management of grid connected photovoltaic system,” Indonesian Journal of Electrical Engineering and Computer Science
(IJEECS), vol. 13, no. 3, pp. 1324-1331, 2019, doi: 10.11591/ijeecs.v13.i3.pp1324-1331.
[8] D. Q. Hung, N. Mithulananthan, and R. C. Bansal, “Analytical expressions for DG allocation in primary distribution networks,”
IEEE Transactions on energy conversion, vol. 25, no. 3, pp. 814-820, 2010, doi: 10.1109/TEC.2010.2044414.
[9] I. S. Kumar and N. P. Kumar. “Optimal planning of distributed generation for improved voltage stability and loss reduction,”
International Journal of Computer Applications, vol. 15, no. 1, pp. 40-46, 2011, doi: 10.5120/1910-2545.
[10] R. P. Payasi, A. K. Singh, and D. Singh, “Review of distributed generation planning: objectives, constraints, and algorithms,”
International journal of engineering, science and technology, vol. 3, no. 3, 2011, doi: 10.4314/ijest.v3i3.68430.
[11] H. Yassami, A. Moeini, S. M. R. Rafiei, A. Darabi, and A. Bagheri. “Optimal distributed generation planning considering
reliability, cost of energy and power loss,” Scientific research and essays, vol. 6, no. 9, pp. 1963-1976, 2011,
doi: 10.5897/SRE10.955.
[12] H. Samet, “Optimal allocation of fault current limiters and distributed generations in the presence of remote controllable
switches,” J. Electrical Systems, vol. 10, no. 2, pp. 149-155, 2014.
[13] M. Abdelbadea, T. A. Boghdady, and D. K. Ibrahim, “Enhancing active radial distribution networks by optimal sizing and
placement of DGs using modified crow search algorithm,” Indonesian Journal of Electrical Engineering and Computer Science
(IJEECS), vol. 16, no. 3, pp. 1179-1188, 2019, doi: 10.11591/ijeecs.v16.i3.pp1179-1188.
[14] T. Bouktir and K. R. Guerriche, “Optimal allocation and sizing of distributed generation with particle swarm optimization
algorithm for loss reduction,” In International Conference and Workshop on Electronics & Telecommunication Engineering
(ICWET), 2015, pp. 59-69.
[15] R. K. Singh, and S. K. Goswami, “Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction,
and voltage improvement including voltage rise issue,” International Journal of Electrical Power & Energy Systems, vol. 32,
no. 6, pp. 637-644, 2010, doi: 10.1016/j.ijepes.2009.11.021.
[16] M. H. Moradi and M. Abedini, “A combination of genetic algorithm and particle swarm optimization for optimal DG location and
sizing in distribution systems,” International Journal of Electrical Power & Energy Systems, vol. 34, no. 1, pp. 66-74, 2012,
doi: 10.1016/j.ijepes.2011.08.023.
[17] S. K. Injeti and N. P. Kumar, “A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium
and large scale radial distribution systems,” International Journal of Electrical Power & Energy Systems, vol. 45, no. 1,
pp. 142-151, 2013, doi: 10.1016/j.ijepes.2012.08.043.
[18] M. Kowsalya, “Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging
optimization,” Swarm and Evolutionary computation, vol. 15, pp. 58-65, 2014, doi: 10.1016/j.swevo.2013.12.001.
[19] D. Shirmohammadi, H. W. Hong, A. Semlyen, and G. X. Luo, “A compensation-based power flow method for weakly meshed
distribution and transmission networks,” IEEE Transactions on power systems, vol. 3, no. 2, pp. 753-762, 1988,
doi: 10.1109/59.192932.
[20] S. K. Injeti, V. K. Thunuguntla, and M. Shareef, “Optimal allocation of capacitor banks in radial distribution systems for
minimization of real power loss and maximization of network savings using bio-inspired optimization algorithms,” International
Journal of Electrical Power & Energy Systems, vol. 69, pp. 441-455, 2015, doi: 10.1016/j.ijepes.2015.01.040.
[21] M. Rostamzadeh, K. Valipour, S. J. Shenava, M. Khalilpour, and N. Razmjooy, “Optimal location and capacity of multi-
distributed generation for loss reduction and voltage profile improvement using imperialist competitive algorithm,” Artificial
Intelligence Research, vol. 1, no. 2, pp. 56-66, Dec. 2012, doi: 10.5430/air.v1n2p56.
[22] I. Hussain, and A. K. Roy, “Optimal distributed generation allocation in distribution systems employing modified artificial bee
colony algorithm to reduce losses and improve voltage profile,” IEEE-International Conference On Advances In Engineering,
Science And Management (ICAESM -2012), 2012, pp. 565-570.
[23] Y. Alinejad-Beromi, M. Sedighizadeh, M. R. Bayat, and M. E. Khodayar, “Using genetic alghoritm for distributed generation
allocation to reduce losses and improve voltage profile,” In 2007 42nd International Universities Power Engineering Conference,
2007, doi: 10.1109/UPEC.2007.4469077.
[24] P. A. D. V. Raj, S. Senthilkumar, J. Raja, S. Ravichandran, and T. G. Palanivelu, “Optimization of distributed generation capacity
for line loss reduction and voltage profile improvement using pso,” Elektrika: Journal of Electrical Engineering, vol. 10, no. 2,
pp. 41-48, 2008.
16. Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752
Energy harvesting maximization by integration of distributed generation … (Tarek A. Boghdady)
625
[25] Z. M. Zenhom, T. A. Boghdady, and H. K. Youssef, “A Proposed Economical Based Approach for Optimal Sizing and Placement
of Distributed Generation,” In 2019 21st International Middle East Power Systems Conference (MEPCON), 2019,
doi: 10.1109/MEPCON47431.2019.9007932.
BIOGRAPHIES OF AUTHORS
Tarek A. Boghdady received the B. S., M. S and Ph. D degrees in electrical
power engineering from the faculty of engineering Cairo University, in 2004, 2010 and 2016.
From 2004 to 2016, he was a teaching assistant in electrical power engineering department in
the same university. Since 2016, he has been an assistant professor in the electrical power
engineering department, Cairo University. He is an author and supervisor of more than thirty
scientific papers. His research interests include wind energy, optimization, power quality,
neural network, fuzzy control, solar energy, sliding mode control, HVDC, and Harmonics. He
can be contacted at email: Engtarek82@gmail.com.
Samar G. A. Nasser received her B. S. degree from Institute of aviation
engineering and technology (I.A.E.T), Giza, Egypt, in 2016. After graduation, she worked
four years as a teaching assistant at I.A.E.T from 2016 to 2020. She is currently working
towards the M. S. degree at the department of electrical power engineering at the faculty of
engineering, Cairo University, Giza, Egypt. She can be contacted at email:
eng_samar_gamal@yahoo.com.
Essam El-Din Aboul Zahab received the B. S., M. S degree in electrical
engineering from Cairo University, faculty of engineering in 1970, 1974 and the Ph. D.
degree in electrical engineering from Paul Sabatier University, France, in 1979. He is
promoted in the academic degrees starting from teaching assistant till being professor
emeritus in electri cal engineering at Cairo University. He is an author and supervisor of
hundreds scientific papers. His research interest switch gear and protection, electrical
distribution system, illumination engineering and electrical power systems. He can be
contacted at email: Zahab0@yahoo.com.