Optimal capacitor placement in distribution system using genetic algorithm

Lohia, Sushma; Mahela, Om Prakash; Ola, Sheesh Ram

doi:10.1109/poweri.2016.8077355

Cited by 16 publications

(14 citation statements)

References 26 publications

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Order By: Relevance

“…Once this order is carried out, the result of the last individual of the matrix is compared with the winning individual according to Equation (14). If the fitness function of the winning individual is less than that of the last individual of the IP, R will take the place corresponding to the loser as long as this individual is different with respect to the other individuals of the IP [3]. If the abovementioned conditions are not complied with, the process will have to be repeated from the selection stage.…”

Section: Replacement Of Individual In the Populationmentioning

confidence: 99%

“…Due to their radial topology, in these systems, a large percentage of power is often lost (i.e., when power energy is transformed to heat energy). Around 70% of the energy losses are presented in power distribution systems, and 13% of the energy delivered to these systems is lost during the distribution stage [3,4]. The author of [5] discussed the amount of money invested in these systems and the type of losses presented; besides, they mentioned that 2/3 parts of the investment in power systems is associated with the distribution, for which distribution is known as "invisible giant" of the power system.…”

Section: Introduction 1general Contextmentioning

confidence: 99%

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Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

et al. 2021

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This study deals with the minimization of the operational and investment cost in the distribution and operation of the power flow considering the installation of fixed-step capacitor banks. This issue is represented by a nonlinear mixed-integer programming mathematical model which is solved by applying the Chu and Beasley genetic algorithm (CBGA). While this algorithm is a classical method for resolving this type of optimization problem, the solutions found using this approach are better than those reported in the literature using metaheuristic techniques and the General Algebraic Modeling System (GAMS). In addition, the time required for the CBGA to get results was reduced to a few seconds to make it a more robust, efficient, and capable tool for distribution system analysis. Finally, the computational sources used in this study were developed in the MATLAB programming environment by implementing test feeders composed of 10, 33, and 69 nodes with radial and meshed configurations.

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Section: Replacement Of Individual In the Populationmentioning

confidence: 99%

Section: Introduction 1general Contextmentioning

confidence: 99%

Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

et al. 2021

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show abstract

“…As seen from Equations (19) and 20, Walk is a control parameter of the method and its value plays an important role in choosing either Equation (19) or Equation (20) to generate a new solution S new X . If Walk is close to 1, there is a very high possibility that the random number Rd x is less than Walk and Equation (19) will be applied.…”

Section: Diffusion Techniquementioning

confidence: 99%

“…To overcome this drawback, an alternative trend of using meta-heuristic methods has been developed for the optimal placement and size of capacitors in distribution networks. Two methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), accompanied by their modified versions [15][16][17][18][19][20] are most popular approaches for this optimization problem. The PSO based methods, including PSO with constriction and inertia weight factors (CIF-PSO) [15], PSO with Multiple Agents (MAs-PSO) [16] and PSO with different applied distributions (DADs-PSO) [17] have been successfully applied, where the best capacitor locations were found according to a factor of loss sensitivity in CIF-PSO [15] and a fuzzy inference in MAs-PSO [16].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, only one small-scale system with 10 nodes was employed to test these methods, and only the Tabu search algorithm (TSA) and conventional GA were shown to have comparable performance. Similarly, GA-based methods including conventional GA [18,19] and modified versions have been introduced where the GA was tested in two small scale systems with 23 nodes and 33 nodes and compared with only PSO based methods and bare systems without compensation. As compared to GA, Real Code-Based GA (RCGA) [20] was applied for more complex cases with 15, 34 and 69-node networks, but its performance was only compared to bare networks without capacitors.…”

Section: Introductionmentioning

confidence: 99%

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Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

et al. 2020

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This paper presents a highly effective method of installing both capacitors and PV systems in distribution systems for the purpose of reducing total power loss in branches. Three study cases with the installation of one capacitor, two capacitors and three capacitors were implemented and then the optimal solutions were used to install one more photovoltaic (PV) system. One PV system with 20% active power of all loads and less than active power of all loads was tested for two different conditions: (1) with geography location constraint and (2) without geography location constraint for PV system placement. The results from two systems consisting of 33 and 69 nodes were obtained by using the Stochastic Fractal Search Optimization Algorithm (SFSOA). Simulation results show that this method can determine the appropriate location and size of capacitors to reduce the total power losses more effectively than other existing methods. Furthermore, the paper also demonstrates the real impact of using both capacitors and PV systems to reduce active power loss as well as improve the voltage profile of distribution systems. This paper also finds that if it is possible to place PV systems in all nodes in distribution systems, the benefit from reducing total loss is highly significant and the investment of PV system placement is highly encouraged. As a result, it is recommended that capacitors and PV systems be used in distribution networks, and we claim that two important factors of the installed components consisting of location and size can be determined effectively by using SFSOA.

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An approach for voltage drop improvement in 22 kV PEA distribution system based on high voltage capacitor placement

Thongsuk,

Ngaopitakkul,

Kotesakha

et al. 2023

Energy Reports

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Optimal capacitor placement in distribution system using genetic algorithm

Cited by 16 publications

References 26 publications

Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization

Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

An approach for voltage drop improvement in 22 kV PEA distribution system based on high voltage capacitor placement

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