The document presents a methodology for optimally placing multiple distributed generators in a distribution network to reduce power losses. It compares two optimization algorithms - the iterative analytical (IA) method and the harmony search algorithm. Both algorithms are tested on 33-bus and 69-bus test systems. The results show that the harmony search algorithm achieves the same or lower power losses compared to the IA method, but with smaller distributed generator sizes.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Impact of Dispersed Generation on Optimization of Power ExportsIJERA Editor
Dispersed generation (DG) is defined as any source of electrical energy of limited size that is connected directly to the distribution system of a power network. It is also called decentralized generation, embedded generation or distributed generation. Dispersed generation is any modular generation located at or near the load center. It can be applied in the form of rechargeable, such as, mini-hydro, solar, wind and photovoltaic system or in the form of fuel-based systems, such as, fuel cells and micro-turbines. This paper presents the impact of dispersed generation on the optimization of power exports. Computer simulation was carried out using the hourly loads of the selected distribution feeders on Kaduna distribution system as input parameters for the computation of the line loss reduction ratio index (LLRI). The result showed that the line loss reduced from 163.56MW to 144.61 MW when DG was introduced which is an indication of a reduction in line losses with the installation of DG at the various feeders of the distribution system. In all the feeders where DG is integrated, the average magnitude of the line loss reduction index is 0.8754 MW which is less than 1 indicating a reduction in the electrical line losses with the introduction of DG. The line loss reduction index confirmed that by integrating DG into the distribution system, the distribution losses are reduced and optimization of power exports is achieved The results of this research paper will form a basis to establish that proper location of distributed generation units have significant impact on their effective capacity.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
BODY ANTENNA WITH DGS FOR BODY CENTRIC WIRELESS COMMUNICATION SYSTEMjantjournal
This paper presents modified patch antenna for 3 GHz and 5 GHz operating frequencies. Here different approaches are studied by varying slot sizes, defected ground size, notch and also changing feed position. Insertion of slots gives dual frequency operation. Notch provides shifting of lower frequency band towards left hand side. Here combined effect of each techniques adopted gives desired result. Proposed antenna resonates for 3 and 5 GHz frequency. Simulation is done using IE3D software for various parameters. Return loss of final design was -12.17 dB for 3 GHz frequency and VSWR of 1.65. For 5 GHz simulation response was -10.04dB return loss and VSWR of 1.91. Proposed antenna is fabricated giving different details. Paper gives good agreement between measured and simulated results.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...ijccsa
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
KEYWORDS
Energy Consumption, Virtual Machine Placement, Harmony Search Algorithm, Server Consolidati
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Impact of Dispersed Generation on Optimization of Power ExportsIJERA Editor
Dispersed generation (DG) is defined as any source of electrical energy of limited size that is connected directly to the distribution system of a power network. It is also called decentralized generation, embedded generation or distributed generation. Dispersed generation is any modular generation located at or near the load center. It can be applied in the form of rechargeable, such as, mini-hydro, solar, wind and photovoltaic system or in the form of fuel-based systems, such as, fuel cells and micro-turbines. This paper presents the impact of dispersed generation on the optimization of power exports. Computer simulation was carried out using the hourly loads of the selected distribution feeders on Kaduna distribution system as input parameters for the computation of the line loss reduction ratio index (LLRI). The result showed that the line loss reduced from 163.56MW to 144.61 MW when DG was introduced which is an indication of a reduction in line losses with the installation of DG at the various feeders of the distribution system. In all the feeders where DG is integrated, the average magnitude of the line loss reduction index is 0.8754 MW which is less than 1 indicating a reduction in the electrical line losses with the introduction of DG. The line loss reduction index confirmed that by integrating DG into the distribution system, the distribution losses are reduced and optimization of power exports is achieved The results of this research paper will form a basis to establish that proper location of distributed generation units have significant impact on their effective capacity.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
BODY ANTENNA WITH DGS FOR BODY CENTRIC WIRELESS COMMUNICATION SYSTEMjantjournal
This paper presents modified patch antenna for 3 GHz and 5 GHz operating frequencies. Here different approaches are studied by varying slot sizes, defected ground size, notch and also changing feed position. Insertion of slots gives dual frequency operation. Notch provides shifting of lower frequency band towards left hand side. Here combined effect of each techniques adopted gives desired result. Proposed antenna resonates for 3 and 5 GHz frequency. Simulation is done using IE3D software for various parameters. Return loss of final design was -12.17 dB for 3 GHz frequency and VSWR of 1.65. For 5 GHz simulation response was -10.04dB return loss and VSWR of 1.91. Proposed antenna is fabricated giving different details. Paper gives good agreement between measured and simulated results.
An Approach to Reduce Energy Consumption in Cloud data centers using Harmony ...ijccsa
Fast development of knowledge and communication has established a new computational style which is
known as cloud computing. One of the main issues considered by the cloud infrastructure providers, is to
minimize the costs and maximize the profitability. Energy management in the cloud data centers is very
important to achieve such goal. Energy consumption can be reduced either by releasing idle nodes or by
reducing the virtual machines migrations. To do the latter, one of the challenges is to select the placement
approach of the migrated virtual machines on the appropriate node. In this paper, an approach to reduce
the energy consumption in cloud data centers is proposed. This approach adapts harmony search
algorithm to migrate the virtual machines. It performs the placement by sorting the nodes and virtual
machines based on their priority in descending order. The priority is calculated based on the workload.
The proposed approach is simulated. The evaluation results show the reduction in the virtual machine
migrations, the increase of efficiency and the reduction of energy consumption.
KEYWORDS
Energy Consumption, Virtual Machine Placement, Harmony Search Algorithm, Server Consolidati
Power consumption is an important metric tool in the context of the wireless sensor networks
(WSNs). In this paper, we described a new Energy-Degree (EDD) Clustering Algorithm for the
WSNs. A node with higher residual energy and higher degree is more likely elected as a
clusterhead (CH). The intercluster and intracluster communications are realized on one hop.
The principal goal of our algorithm is to optimize the energy power and energy load among all
nodes. By comparing EDD clustering algorithm with LEACH algorithm, simulation results
have showen its effectiveness in saving energy.
NOVEL BAND-REJECT FILTER DESIGN USING MULTILAYER BRAGG MIRROR AT 1550 NMcscpconf
Novel band-reject filter is proposed using multilayer Bragg mirror structure by computing reflection coefficient at 1550 nm wavelength for optical communication. Dimension of different
layers and material composition are modified to study the effect on rejection bandwidth, and no of layers is also varied for analyzing passband characteristics. GaN/AlxGa1-xN composiiton is taken as the choice for simulation purpose, carried out using propagation matrix method. Refractive indices of the materials are considered as function of bandgap, perating wavelength and material composition following Adachi’s model. One interesting result arises from the computation that band-reject filter may be converted into band-pass one by suitably varying ratio of thicknesses of unit cell, or by varying Al mole fraction. Simulated results can be utilised to design VCSEL mirror as optical transmitter.
Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch...ijeei-iaes
In this paper, a new method, called Atmosphere Clouds Model (ACM) algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss.
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.
Mutual Coupling Reduction between Asymmetric Reflectarray Resonant Elements IJECEIAES
A physically asymmetric reflectarray element has been proposed for wide band operations. The dual resonant response has been introduced by tilting one side of the square path element. The numerical results have been analyzed in the frequency band between 24GHz to 28GHz where a reflection phase range of more than 600° has been achieved. The proposed asymmetric element can produce mutual coupling with adjacent elements on a reflectarray. This effect has been monitored by placing the elements in a mirror configuration on the surface of reflectarray. The single unit cell element results have been compared with conventional 4 element unit cell and proposed mirroring element configuration. The proposed mirroring element technique can be used to design a broadband reflectarray for high gain applications.
Este boletín te ayudará a concer más sobre la gestión de proyectos y cómo es que se puede aplicar en la vida diaria. Así mismo enontraras información útil sobre PMI y los procesos que lleva a cabo.
Power consumption is an important metric tool in the context of the wireless sensor networks
(WSNs). In this paper, we described a new Energy-Degree (EDD) Clustering Algorithm for the
WSNs. A node with higher residual energy and higher degree is more likely elected as a
clusterhead (CH). The intercluster and intracluster communications are realized on one hop.
The principal goal of our algorithm is to optimize the energy power and energy load among all
nodes. By comparing EDD clustering algorithm with LEACH algorithm, simulation results
have showen its effectiveness in saving energy.
NOVEL BAND-REJECT FILTER DESIGN USING MULTILAYER BRAGG MIRROR AT 1550 NMcscpconf
Novel band-reject filter is proposed using multilayer Bragg mirror structure by computing reflection coefficient at 1550 nm wavelength for optical communication. Dimension of different
layers and material composition are modified to study the effect on rejection bandwidth, and no of layers is also varied for analyzing passband characteristics. GaN/AlxGa1-xN composiiton is taken as the choice for simulation purpose, carried out using propagation matrix method. Refractive indices of the materials are considered as function of bandgap, perating wavelength and material composition following Adachi’s model. One interesting result arises from the computation that band-reject filter may be converted into band-pass one by suitably varying ratio of thicknesses of unit cell, or by varying Al mole fraction. Simulated results can be utilised to design VCSEL mirror as optical transmitter.
Atmosphere Clouds Model Algorithm for Solving Optimal Reactive Power Dispatch...ijeei-iaes
In this paper, a new method, called Atmosphere Clouds Model (ACM) algorithm, used for solving optimal reactive power dispatch problem. ACM stochastic optimization algorithm stimulated from the behavior of cloud in the natural earth. ACM replicate the generation behavior, shift behavior and extend behavior of cloud. The projected (ACM) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the superior performance of the proposed algorithm in plummeting the real power loss.
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.
Mutual Coupling Reduction between Asymmetric Reflectarray Resonant Elements IJECEIAES
A physically asymmetric reflectarray element has been proposed for wide band operations. The dual resonant response has been introduced by tilting one side of the square path element. The numerical results have been analyzed in the frequency band between 24GHz to 28GHz where a reflection phase range of more than 600° has been achieved. The proposed asymmetric element can produce mutual coupling with adjacent elements on a reflectarray. This effect has been monitored by placing the elements in a mirror configuration on the surface of reflectarray. The single unit cell element results have been compared with conventional 4 element unit cell and proposed mirroring element configuration. The proposed mirroring element technique can be used to design a broadband reflectarray for high gain applications.
Este boletín te ayudará a concer más sobre la gestión de proyectos y cómo es que se puede aplicar en la vida diaria. Así mismo enontraras información útil sobre PMI y los procesos que lleva a cabo.
Placement of Multiple Distributed Generators in Distribution Network for Loss...IJMTST Journal
This paper presents a methodology for multiple distributed generator (DG) placement in primary distribution network for loss reduction. Optimal location for distributed generator (DG) is selected by Analytical expressions and the optimal DG size calculated by IA method and loss sensitivity factor (LSF). These two methods are tested on two test systems 33-bus and 69-bus radial distribution systems. The final results showed that LSF gives same loss reduction and minimum voltage in the system with less DG size than obtained in IA method.
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.
Loss Reduction by Optimal Placement of Distributed Generation on a Radial feederIDES Editor
Due to the increasing interest on renewable sources
in recent times, the studies on integration of distributed
generation to the power grid have rapidly increased. In order
to minimize line losses of power systems, it is crucially
important to define the location of local generation to be placed.
Proper location of DGs in power systems is important for
obtaining their maximum potential benefits. This paper
presents analytical approaches to determine the optimal
location to place a DG on radial systems to minimize the power
loss of the system. Simulation results are given to verify the
proposed analytical approaches.
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.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
These slides presents an introduction to distributed generators integration in distribution system. Later its modelling, control, protection aspects will be presented.
Optimal Siting of Distributed Generators in a Distribution Network using Arti...IJECEIAES
Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
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.
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.
In this paper a load flow based method using MATLAB Software is used to determine the optimum location and optimum size of DG in a 43-bus distribution system for voltage profile improvement and loss reduction. This paper proposes analytical expressions for finding optimal size of three types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. Single DG installation case was studied and compared to a case without DG, and 43-bus distribution system is used to demonstrate the effectiveness of the proposed method. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of injecting real power only, DG capable of injecting reactive power only and DG capable of injecting both real and reactive power can also be identified with their optimal size and location using the proposed method. This paper has been analysed with varying DG size and complexity and validated using analytical method for Summer case and Winter case in 43-bus distribution system in Myanmar.
Keywords- analytical method,distributed generation,power loss reduction,voltage profile improvement.
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 Expenditure and Benefit Cost Based Location, Size and Type of DGs in ...TELKOMNIKA JOURNAL
The economic issue is an essential element to determine whether DG should be installed or not. This work presents the economical approach for multi-type DGs placement in microgrid systems with more comprehensive overview from DG’s owner perspective. Adaptive Real Coded GA (ARC-GA) with replacement process is developed to determine the location, type, and rating of DGs so as the maximum profit is achieved. The objectives of this paper are maximizing benefit cost and minimizing expenditure cost. All objectives are optimized while maintaining the bus voltage at the acceptable range and the DGs penetration levels are below of the DGs capacities.The proposed method is applied on the 33 bus microgrids systems using conventional and renewable DG technology, namely Photovoltaic (PV), Wind Turbine (WT), Micro Turbine (MT) and Gas Turbine (GT). The simulation results show the effectiveness of the proposed approach.
Optimal Placement and Sizing of Capacitor and Distributed Generator in Radial...IJMTST Journal
Distribution Systems are growing large and being stretched too far, leading to higher system losses and
poor voltage regulation, the need for an efficient and effective distribution system has therefore become more
urgent and important. A distribution system connects consumers to the high-voltage transmission system.
Because of lower voltage, and hence higher current, the I2R loss in a distribution system is significantly high
compared to that in a high-voltage transmission system. The pressure of improving the overall efficiency of
power delivery has forced the power utilities to reduce the loss, especially at the distribution level. Loss
reduction initiatives in distribution systems have been activated due to the increasing cost of supplying
electricity, the shortage in fuel with ever-increasing cost to produce more power, and the global warming
concerns. The total system loss can be decreased by installing capacitor bank and distributed generation.
These two methods can also help maintaining the level of voltage and maintenance power factor. The direct
search algorithm is applied to minimize the loss in radial distribution systems.
Performance comparison of distributed generation installation arrangement in ...journalBEEI
Placing Distributed Generation (DG) into a power network should be planned wisely. In this paper, the comparison of having different installation arrangement of real-power DGs in transmission system for loss control is presented. Immune-brainstorm-evolutionary programme (IBSEP) was chosen as the optimization technique. It is found that optimizing fixed-size DGs locations gives the highest loss reduction percentage. Apart from that, scattered small-sized DGs throughout a network minimizes transmission loss more than allocating one biger-sized DG at a location.
Multi-objective whale optimization based minimization of loss, maximization o...IJECEIAES
Huge need in electricity causes placement of Distribution Generation (DG)s like Photovoltaics (PV) systems in distribution side for enhancing the loadability by improving the voltage stability and minimization of loss with minimum cost. Many optimal placements of DG have done in focus of minimum loss and improving voltage profile. This Whale optimization is a new optimization technique framed with mathematics of spiral bubble-net feeding behavior of humpback whales for solving a power system multi-objective problem considering cost of the power tariff and DG. Here main objectives are minimizing loss and cost with maximization of voltage stability index. IEEE 69 power system data is used for solution of the proposed method.
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.
Voltage Profile Improvement of distribution system Using Particle Swarm Optim...IJERA Editor
Distributed generations (DGs) play an important role in distribution networks. Distributed generation (DG) exists in distribution systems and is installed by either the utility or the customers. Distributed Generators (DGs) are now commonly used in distribution systems to reduce the power disruption in the power system network. Due to the installation of DGs in the system, the total power loss can be reduced and voltage profile of the buses can be improved due to this power quality of the distribution system is improved. Studies show that non-optimal locations and non-optimal sizes of DG units may lead to losses increase, together with bad effect on voltage profile. So, this paper aims at determining optimal DG allocation and sizing. To do so, the optimization technique named Particle Swarm Optimization (PSO) is used .this Particle Swarm Optimization (PSO) approach), capable to establish the optimal DG allocation and sizing on a distribution network. This paper presents optimal placement and estimation of distributed generation (DG) capacity using Particle Swarm Optimization (PSO) approach in the distribution systems to reduce the real power losses and to gain voltage profile improvement. The proposed (PSO) based approach is tested on an IEEE 30-bus test system.
Voltage Profile Improvement of distribution system Using Particle Swarm Optim...
Hc2512901294
1. K.Srinivasa Rao, M.Nageswara Rao / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1290-1294
Optimal Placement Of Multiple Distributed Generator By Hs
Algorithm
K.Srinivasa Rao 1 M.Nageswara Rao 2
1
University College of engineering, JNTU, Kakinada, India.
2
University College of engineering, JNTU, Kakinada, India.
Abstract
This paper presents a methodology for some or all of the required power without the need
multiple distributed generator (DG) placement in for increasing the existing traditional generation
primary distribution network for loss reduction. capacity or T&D system expansion. DG capital cost
Optimal location for distributed generator (DG) is not large due to its moderate electric size and
is selected by Analytical expressions and the modular behavior as it can be installed
optimal DG size calculated by IA method and incrementally unlike installing new substations and
Harmony search algorithm. These two methods feeders, which require large capital cost to activate
are tested on two test systems 33-bus and 69-bus the new expanded distribution system [12]. The
radial distribution systems. The final results technical benefits include improvement of voltage,
showed that harmony search algorithm gives loss reduction, relieved transmission and
same loss reduction and minimum voltage in the distribution congestion, improved utility system
system with less DG size than obtained in IA reliability and power quality [6] and increasing the
method. durability of equipment, improving power quality,
Index Terms—IA method, Harmony search, total harmony distortion networks and voltage
optimal location, Optimal DG size, Multiple DG, stability by making changes in the path through
Analytical Expressions, Distributed generation. which power passes [9].These benefits get the
optimum DG size and location is selected.
I. INTRODUCTION Distributed system planning using distributed
The central power plants are thermal, generation [12]. If the DG units are improperly sized
nuclear or hydro powered and their rating lies in the and allocated leads to real power losses increases
range of several hundred MW‟s to few GW‟s [2]. than the real power loss without DG and reverse
central power plants are economically unviable in power flow from larger DG units. So, the size of
many areas due to diminishing fossil fuels, distribution system in terms of load (MW) will play
increasing fuel costs, and stricter environmental important role is selecting the size of DG. The
regulations about acid deposition and green house reason for higher losses and high capacity of DG
gas emission[3].smaller power plants with a few can be explained by the fact that the distribution
dozens of MW‟s, instead of few GW‟s, became system was initially designed such that power flows
more economical[2]. Also, generators with from the sending end (source substation) to the load
renewable sources as wind or solar energy became and conductor sizes are gradually decreased from
more economically and technically feasible. This the substation to consumer point. Thus without
has resulted in the installation of small power plants reinforcement of the system, the use of high
connected to the distribution side of the network, capacity DG will lead to excessive power flow
close to the customers and hence referred to as through small sized conductors and hence results in
“embedded” or “distributed” generation (DG). higher losses.[7]
Sometimes it is also called “dispersed generation” or Different techniques are proposed by
“decentralized generation”. [4]. authors the techniques are, a technique for DG
Distributed generation technologies are placement using “2/3 rule” which is traditionally
renewable and nonrenewable. Renewable applied to capacitor allocation in distribution
technologies include solar, photovoltaic or thermal, systems with uniformly distributed loads has been
wind, geothermal, ocean. Nonrenewable presented. Although simple and easy to apply, this
technologies include internal combustion engine, technique cannot be applied directly to a feeder with
ice, combined cycle, combustion turbine, micro other types of load distribution or to a meshed
turbines and fuel cell. [5] Most of the DG energy distribution system. The genetic algorithm (GA)
sources are designed using green energy which is based method has been presented to determine the
assumed pollution free [6]. size and location of DG. GA is suitable for multi-
Installing DGs at the load centers will objective problems and can lead to a near optimal
prevent the new transmission lines extension to solution, but demand higher computational time. An
energize new substation, DG is capable of providing analytical approach based on an exact loss formula
has been presented to find the optimal size and
1290 | P a g e
2. K.Srinivasa Rao, M.Nageswara Rao / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1290-1294
location of single DG. A probabilistic-based without updating the 𝛼 and 𝛽 the results are same
planning technique has been proposed for [1].
determining the optimal fuel mix of different types B. Optimal DG size selection:
of renewable DG units (i.e., wind, solar, and The Distributed generator is placed at the
biomass) in order to minimize the annual energy optimum location. The optimum DG size is selected
losses in the distribution system [1]. by varying the DG in small steps up to the point
where real power loss is minimum. The real power
II. PROBLEM FORMULATION loss is calculated by “back ward forward sweep”
This section describes to find the optimum load flow algorithm.
size and location of distributed generator.
A. Selection of Location: III. IA METHOD
Find the best bus for the placement of DG, The computational procedure of IA method
The DG sizes at each bus is calculated by using is as follows:
(2).The DG‟s are placed at each bus and calculate Step 1: Enter the number of DG units to be
the real power loss by (1).The bus which has installed.
minimum real power loss is selected as best location Step 2: Run load flow for the base case and find
for placement of DG. losses using (1).
The real power loss in a system can be calculated by Step 3: Find these optimal location of DG using the
(1). This is also called as “Exact loss formula” [13]. following steps.
𝑁 𝑁
a) Calculate the optimal size of DG at each
𝑃𝐿 = [𝛼 𝑖𝑗 𝑃𝑖 𝑃𝑗 + 𝑄 𝑖 𝑄 𝑗 + 𝛽𝑖𝑗 𝑄 𝑖 𝑃𝑗 − 𝑃𝑖 𝑄 𝑗 ] (1) bus using (2) and (3).
𝑖=1 𝑗 =1 b) Place the DG with the optimal size as
Where mentioned earlier at each bus, one at a
𝑟 𝑖𝑗
𝛼 𝑖𝑗 = cos 𝛿 𝑖 − 𝛿𝑗 ; time. Calculate the approximate loss for
𝑣𝑖 𝑣𝑗
𝑟 𝑖𝑗
each case using (1).
𝛽𝑖𝑗 = sin 𝛿 𝑖 − 𝛿𝑗 ; c) Locate the optimal bus at which the loss
𝑣𝑖 𝑣𝑗
is at minimum.
𝑟𝑖𝑗 + 𝑗𝑥 𝑖𝑗 = 𝑍 𝑖𝑗 ijth element of [Zbus] impedance
Step 4: Find the optimal size of DG and calculate
matrix;
losses using the following steps.
N is number of buses
a) Place a DG at the optimal bus obtained
Where Pi and Qi are Real and Reactive power in step 4, change this DG size in small
injections at node „i‟ respectively. step, and calculate the loss for each case
Real power injection is the difference between Real using “Back ward forward” load flow.
power generation and the real power demand at that
b) Select and store the optimal size of the
node.
DG that gives the minimum loss.
𝑃𝑖 = (𝑃 𝐷𝐺𝑖 − 𝑃 𝐷𝑖 ) Step 5: Update load data after placing the DG with
𝑄 𝑖 = (𝑄 𝐷𝐺𝑖 − 𝑄 𝐷𝑖 ) the optimal size obtained in step 5 to
Where, 𝑃 𝐷𝐺𝑖 and 𝑄 𝐷𝐺𝑖 is the real power injection allocate the next DG.
and reactive power injection from DG placed at Step 6: Stop if either the following occurs
node i respectively. 𝑃 𝐷𝑖 and 𝑄 𝐷𝑖 are load demand at a) the voltage at a particular bus is over the
the node i respectively [14]. upper limit
𝛼 𝑖𝑖 𝑃 𝐷𝑖 + 𝑎𝑄 𝐷𝑖 − 𝑋 𝑖 − 𝑎𝑌𝑖 b) The total size of DG units is over the
𝑃 𝐷𝐺𝑖 = (2)
𝑎2 𝛼 𝑖𝑖 + 𝛼 𝑖𝑖 total plus loss
𝑄 𝐷𝐺𝑖 = ± (tan( cos−1 (𝑃𝐹 𝐷𝐺 ))) ∗ 𝑃 𝐷𝐺𝑖 (3) c) The maximum number of DG units is
Where unavailable
𝑛
d) The new iteration loss is greater than the
𝑋𝑖 = 𝛼 𝑖𝑖 𝑃𝑗 − 𝛽𝑖𝑗 𝑄 𝑗 previous iteration loss. The previous
𝑗 =1 iteration loss is retained otherwise, repeat
𝑗 ≠𝑖
𝑛 steps 2 to6.
𝑌𝑖 = 𝛼 𝑖𝑖 𝑄 𝑗 + 𝛽 𝑖𝑗 𝑃𝑗
𝑗 =1
IV. HARMONY SEARCH ALGORITHM
𝑗 ≠𝑖 The harmony search algorithm (HSA) is a
„+‟ sign for injecting Reactive power new meta-heuristic algorithm. The harmony search
„- „sign for consuming Reactive power algorithm (HSA) is simple in concept, few in
The exact loss formula is a function of loss parameters and easy in implementation. Harmony
coefficients 𝛼 and 𝛽.These coefficients depends on search algorithm is concept from natural musical
magnitude of voltage and voltage angle at each bus. performance processes [8]. In music improvisation,
So for every DG placement at each bus the 𝛼 and 𝛽 each musician plays within possible pitches to make
changes so for that every time requires load flow a harmony vector. If all the pitches create good
calculation. But the results show that with and harmony, the musician saved them in memory and
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3. K.Srinivasa Rao, M.Nageswara Rao / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1290-1294
' with probabilit y HMCR
increases good or better harmony for next time.
Similarly, in the field of engineering optimization, at xi
first each decision variable value is selected within with probabilit y (1 - HMCR)
the possible range and formed a solution vector. If A PAR of 0.3 indicates that the algorithm will
all decision variable values lead to a good solution, choose a neighboring value with 30% × HMCR
each variable that has been experienced is saved in probasbility.
memory and it increases the possibility of good or Step 4: Update the HM
better solutions for next time. Both processes intend In this stage, if the New Harmony vector is
to produce the best or optimum better than the worst harmony vector in the HM in
Step 1: Initialize the optimization problem and terms of the objective function value, the existing
algorithm parameters worst harmony is replaced by the New Harmony.
In this step the optimization problem is specified as Step 5: Repeat steps 3 and 4 until the termination
follows: criterion is satisfied
Minimize f(x) Termination criterion:
Subject to xi ∈Xi, = 1, 2, ..., N The computations are terminated when the
where f(x) is the objective function; x is a candidate termination criterion (maximum number of
solutions consisting of N decision variables (xi); Xi improvisations) is satisfied. Otherwise, steps 3
is the set of possible range of values for each (improvising New Harmony from the HM) and 4
decision variable, that is, Lxi≤Xi≤Uxi for (updating the HM) are repeated [9].
continuous decision variables where Lxi and Uxi are
the lower and upper bounds for each decision V. RESULTS AND ANALYSIS
variable, respectively and N is the number of In this paper IA method and Harmony
decision variables. In addition, HS algorithm search algorithm are tested on 33-bus [10] and 69-
parameters that are required to solve the desired bus [11] radial distribution system. Here Type 3 [1]
optimization problem are specified in this step. DG is considered
Step 2: Initialize the Harmony Memory (HM) A. Assumptions
In this step, the Harmony Memory (HM The assumptions for this paper are as follows:
matrix), is filled with as many randomly generated 1. The maximum number of DG units is
solution vectors as HMS and sorted by the values of three, with the size each from 250KW to
the objective function. the total load plus loss.
Step 3: Improvise a new harmony from the HM 2. The maximum voltage at each bus is 1.0
A New Harmony vector is generated from p.u.
the HM based on memory considerations, pitch B. 33-Bus system
adjustments, and randomization. For instance, the The simulation results of the optimal
value of the first decision variable for the new location and optimal sizing of DG shown in Table-I.
vector can be chosen from any value in the specified The real power loss of 33-bus system is 211kW
HM range Values of the other decision variables can without DG. In single DG placement by IA method
be chosen in the same manner. There is a possibility the DG size is 2.6 MW and in case of Harmony
that the new value can be chosen using the HMCR search algorithm 2.5MW, the real power loss is 111
parameter, which varies between 0 and 1 as follows: kW. In case of 2 DG‟s placement the DG size by IA
' 1 2
' xi xi ,xi ,........xi
xi
HMS
with probabilit y HMCR method 1.9 MW, 0.6 MW and Harmony search
algorithm 1.6 MW, 0.7 MW, the real power loss is
x'i X i with probabilit y (1 HMCR) 91.55 kW. In case of 3 DG‟s placement the DG size
by method 1.3 MW, 0.6 MW, 0.6 MW and by
The HMCR sets the rate of choosing one Harmony search algorithm 1.5 MW, 0.5 MW, 0.3
value from the historic values stored in the HM and MW, the real power loss is 79.69 kW.
(1-HMCR) sets the rate of randomly choosing one
feasible value not limited to those stored in the HM. TABLE-I
For example, a HMCR of 0.9 indicates that the HS COMPARISON OF DIFFERENT TECHNIQUES
algorithm will choose the decision variable value ON 33-BUS SYSTEM
from historically stored values in the HM with the
90% probability or from the entire possible range
with the 10% probability. Each component of the
New Harmony vector is examined to determine
whether it should be pitch adjusted. This procedure
uses the PAR parameter that sets the rate of
adjustment for the pitch chosen from the HM as
follows:
Pitch adjusting decision for
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4. K.Srinivasa Rao, M.Nageswara Rao / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1290-1294
Cases DG With With DG
VI. CONCLUSION
schedule out
1 DG 2 3 In this paper harmony search algorithm is
DG
DG‟s DG‟s proposed for multiple DG placement. The DG
location is finding by IA expressions and the
Optimum ----- 6 6 6
optimum DG size is finding by IA method and HSA
Bus 15 15
algorithm. The results are compared with IA
33
method. Results shows that HSA algorithm gives
DG size ----- 2.6 1.9 1.3 same real power loss and voltage with less DG size
(MW) 0.6 0.6
occurred in IA method.
IA 0.6
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BIOGRAPHY
K.srinivasa Rao is pursuing M.Tech in Department
of Electrical Engineering, Jawaharlal Nehru
Technological University, Kakinada, India. His areas
of interest include electrical power systems and
Renewable energy resources.
M.Nageswara Rao is Assistant Professor in the
Department of Electrical Engineering, Jawaharlal
Nehru Technological University, Kakinada, India.
His areas of interest include electric power
distribution systems and AI Techniques applied to
power systems.
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