Optimal Capacitor Allocation and Sizing in Distribution Networks Using Particle Swarm Optimization Algorithm

Mendoza, G. E.; Vacas, V. M.; Ferreira, Niraldo Roberto

doi:10.1109/wcnps.2018.8604320

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…In order to avoid this situation, several improvements can be made to the inertia weight value, such as utilizing the concept of "a time-decreasing inertia weight" theorem [5]. This concept has the ability to expedite the convergence of particles toward the ideal solution and hence decrease the number of iterations required.…”

Section: Researc Methods 21 Modified Particle Swarm Optimization (Mpso)mentioning

confidence: 99%

The Optimal Capacitors Allocation and Sizing in Radial Distribution System for Power Losses Reduces

Astrid,

Solihin,

Siregar

et al. 2023

JTEIN

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The use of capacitors in electrical systems is widely known for their function to improve power factor and voltage profile while minimizing power losses. It results from the reactive power correction provided by capacitors within the system. It is believed that proper placement and size of capacitors can enhance the electricity quality in power systems. Therefore, numerous methods have been developed regarding the allocation and sizing of capacitors. In this research, a meta-heuristic method, Particle Swarm Optimization (PSO) is applied to find the optimal allocation and sizing of capacitors in order to reduce losses. The method has also been improved by modifying the value of inertia weight to optimize the algorithm's performance in finding the solution. The method is tested on an IEEE 34 bus radial distribution system to observe its performance and effectiveness in identifying the solution. The power loss in the distribution system plays the most important role in the economic operation of the power system. It will be used as a fitness function for each particle in the algorithm. The obtained test results include the size of the capacitor and the optimal placement of the capacitor installation.

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Section: Researc Methods 21 Modified Particle Swarm Optimization (Mpso)mentioning

confidence: 99%

The Optimal Capacitors Allocation and Sizing in Radial Distribution System for Power Losses Reduces

Astrid,

Solihin,

Siregar

et al. 2023

JTEIN

View full text Add to dashboard Cite

show abstract

“…Capacitors are generally the most economical; hence they attract more studies. Chunks of research such as in [37]- [43] worked on the optimal sizing and allocation of capacitors in a distributed network through the use of meta-heuristic algorithms. Other power electronic devices such as STATCOM, which consists of coupling transformers, energy storage devices, and inverters [44], have also been optimally placed and sized.…”

Section: B Power Electronic Unitsmentioning

confidence: 99%

“…The study can be further extended by evaluating the algorithm on a test bus system and comparing with other algorithms. In [43], PSO was suggested to optimally size and allocate capacitors in a distribution network, to reduce real power losses and economic costs. The algorithm was evaluated on 34-bus and 85-bus system, and results from a comparison with the WOA show that the PSO had higher voltage profile improvement.…”

Section: B Swarm-based Algorithmsmentioning

confidence: 99%

A Review of Metaheuristic Techniques for Optimal Integration of Electrical Units in Distribution Networks

et al. 2021

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“…Table 1 lists the results of capacitor placement for 33-bus distribution network obtained by different indices, namely, LSF, LSI 1 , LSI 2 , LSI and TLI when 2, 3, 4, 5 problem is solved by the optimizer with respect to the determined high potential buses (capacitor placement on the other buses is ignored). When two buses are considered, candidate buses based on LSF, LSI 1 , LSI 2 , LSI, and TLI are (28, 29), (3,6), (6,28), (3,6) and (30, 33), respectively. In this case, after doing the second level, it is observed that the minimum objective function value belongs to TLI (76 068.44 $).…”

Section: F I G U R E 5 Schematic Of 33-bus Distribution Networkmentioning

confidence: 99%

“…Although GA is a population‐based algorithm, which usually leads to better results than trajectory‐based algorithms, it suffers from premature convergence owing to the loss of population diversity at early stages of search process. Particle swarm optimization (PSO) has been applied to CPP in Reference 5, 6. Like GA, PSO is a population‐based algorithm which suffers from stagnation and may be trapped in local optima when the system under consideration is large.…”

Section: Introductionmentioning

confidence: 99%

A new analytical index for solving capacitor placement problem of distribution networks in bi‐level framework: Total loss index

Montazeri

Askarzadeh

2020

Int Trans Electr Energ Syst

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Capacitor allocation of distribution network is a complex and highdimensional optimization problem. As a result, most often, optimization techniques are entangled in local optima. To overcome this problem, this article presents a new bi-level framework for capacitor allocation: (a) at the first level, a new analytical index, named total loss index (TLI), has been proposed to identify high potential buses; and (b), at the second level, a metaheuristic optimization, crow search algorithm (CSA), has been applied for finding the best solution among the candidate solutions. TLI, which depends on the network topology, considers the sensitivity of the network losses to reactive power injection. The proposed framework (TLI + CSA) has been tested on 33-bus and 69-bus radial distribution networks. It is observed that reduction of search space will increase the probability of finding global solution so that (a) on 33-bus network, when three high potential buses are identified at the first level, the optimizer can find the global solution at the second level and (b) on 69-bus network, when six high potential buses are identified by TLI, CSA can find the global solution. It can be drawn that using the proposed TLI + CSA leads to finding more accurate results than the other methodologies. K E Y W O R D S bi-level optimization, capacitor placement, crow search algorithm, radial distribution network, total loss index 1 | INTRODUCTION Capacitor placement problem (CPP) is one of the most important issues for distribution network planners. CPP is defined as the optimal determination of location, type and size of shunt capacitors to reach different goals such as minimization of power losses, improvement of voltage profile and correction of power factor. These objectives are considered with respect to List of symbols and abbreviations: C c , Capacitor cost; C cI , Installation cost; C e , Average cost per unit of power loss ($/kWh); F, Objective function; I k , Current of branch k; LR i , Value of bus reduction at bus i; N B , Number of candidate buses; N L , Number of load buses; P i , Total effective active power supplied to bus i; P Loss , Total network active power loss; PF min , Lower limit of power factor; PF overall , Power factor; Q i , Capacitor bank rating at bus i; Q min Ci , Lower reactive power limit of compensated bus i; Q max Ci , Upper reactive power limit of compensated bus i; Q Ci , Reactive power injected to bus i; Q d, i , Reactive power demand at load bus i; R ij , Resistance between buses i and j; S Li , Actual line flow; S rated Li , Rated line capacity; T, Time period; jV i j, Voltage magnitude at bus i.

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Optimal Capacitor Allocation and Sizing in Distribution Networks Using Particle Swarm Optimization Algorithm

Cited by 8 publications

References 9 publications

The Optimal Capacitors Allocation and Sizing in Radial Distribution System for Power Losses Reduces

The Optimal Capacitors Allocation and Sizing in Radial Distribution System for Power Losses Reduces

A Review of Metaheuristic Techniques for Optimal Integration of Electrical Units in Distribution Networks

A new analytical index for solving capacitor placement problem of distribution networks in bi‐level framework: Total loss index

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