Capacitor Placement In Distribution Systems Research Articles

Optimizing Capacitor Placement in Distribution Systems Under Variable Loading Conditions with Golden Jack Optimization (GJO)

In modern society, the demand for electricity is ever-growing, making the minimization of power losses in distribution systems paramount. One significant aspect contributing to these losses is the strategic placement of capacitors within the distribution network. Efficient capacitor placement not only reduces power losses but also enhances the overall performance and reliability of the system. In today's world, where electricity is indispensable, minimizing power losses in the distribution system holds significant importance. This research introduces the Golden Jack Optimization (GJO) algorithm as a novel approach to address the challenge of capacitor placement in distribution systems. GJO, inspired by the foraging behavior of jackals, exhibits unique characteristics such as adaptability and efficiency in finding optimal solutions this paper proposes an innovative algorithm specifically designed for this purpose. To validate the effectiveness of the algorithm, extensive testing and experimentation have been conducted on the IEEE 69-bus system. This study aims to provide a practical and efficient solution to the challenge of power loss reduction within distribution systems. By harnessing the power of GJO and the insights gained from testing on the IEEE 69-bus system, we contribute to the ongoing efforts to enhance the efficiency and sustainability of electricity distribution networks. The results are compared with MPSO, TSM, GA-Fuzzy algorithms and proposed algorithm shows superior performance.

An Extensive Literature Review and New Proposal on Optimal Capacitor Placement in Distribution Systems

The main goal of power utilities is to supply reliable and quality power to the end-users and fulfill their total demands at all possible locations. Most of the loads are connected in the distribution systems are inductive. The excessive reactive power demand over the distribution network causes tremendous reactive power losses and changes the voltage profile, hence the system's reliability. Shunt Capacitor Bank (SCB) is widely used in the distribution system for reactive power support, voltage profile, and system performance improvement. But there are some challenges to employ SCB in the distribution network; among them, ensuring the most optimum location and size is a big challenge to get the maximum benefits. Some existing techniques showed better loss reduction but needed either larger SCBs sizes or cause improper node voltage. In this research study, the first section provides an extensive literature review of optimal SCBs placement and sizing. Later on, a new technique called Combinatorial Method has been developed for sizing and sitting of optimal Shunt Capacitors to reduce the distribution loss significantly. The developed method was tested for different case studies using Indian practical 22-bus and IEEE-69-bus network. The results were compared with DSA, Fuzzy GA, and TLBO method and found better distribution feeder loss minimization and voltage profile improvement.

Optimal unbalanced capacitor placement in distribution systems for voltage control and energy losses minimization

This paper describes an allocation methodology for capacitor placement in unbalanced distribution systems to achieve loss minimization with an adequate voltage profile. Switched capacitor banks and/or fixed banks can be allocated on a per-phase or multi-phase, discrete basis, and this allows consideration of the actual unbalanced characteristics of distribution systems. While most methods available in the literature address some specific network loading conditions, e.g. average, light-load or heavy-load, the proposed algorithm is based on the daily load variation curve. The method consists of two main steps: (i) reactive power demand calculation to achieve loss minimization; (ii) discrete capacitor placement. The method is applied on the IEEE 4-bus, IEEE 123-bus and IEEE NEV Test Feeders as well as on an 85-bus feeder. Several alternative allocations are calculated and comparisons with results available in the literature are presented.

Optimal capacitor placement in distorted distribution systems considering resonance constraint using multi‐swarm particle swarm optimisation algorithm

Optimal capacitor placement in distribution systems has been studied for many reasons such as the improvement of voltage profile, mitigation of total harmonic distortion, and reduction of power losses. In this study, a new approach is presented for capacitor placement in the presence of harmonic distortion along with a proposed resonance index (RI). In this approach, a sensitivity analysis is first applied to find candidate buses. After that, the size and location of capacitors are optimised by a proposed fitness function. The fitness function includes a fuzzy membership function of annual net benefit, maximum THD of voltage, maximum voltage deviation, and a resonance constraint. This procedure supports different load levels employing fixed and switched capacitors. Also, a new RI is presented to prevent resonance conditions. Finally, the approach is tested on an IEEE 18-bus and an IEEE 69-bus system using the multi-swarm particle swarm optimisation algorithm. The simulation results show the efficiency of the method in comparison with the other methods.

Hybrid Symbiotic Organisms Search for Optimal Fuzzified Joint Reconfiguration and Capacitor Placement in Electric Distribution Systems

Network reconfiguration and capacitor allocation are two valuable tools to optimally manage distribution systems. In the present work, an efficient algorithm is proposed for the joint problem of reconfiguration and capacitor placement in distribution systems. The multi-objective problem is formulated to minimize objective functions of total network power losses, bus voltage violation, and branch loading deviations subject to different technical and operational constraints. To enhance exploration ability, the Symbiotic Organisms Search algorithm is strengthened with Particle Swarm Optimization capabilities to develop the Hybrid Symbiotic Organisms Search algorithm, which is applied to solve the proposed problem. Objective functions are fuzzified and aggregated by a geometric mean operator to have the same scales. The proposed joint optimization problem is solved with the introduced Hybrid Symbiotic Organisms Search algorithm in two different case studies of balanced and unbalanced test systems. According to obtained results that are compared with some well-known evolutionary algorithms, the superiority of the Hybrid Symbiotic Organisms Search algorithm is confirmed in terms of solution optimality and convergence speed.

Capacitor placement in distribution systems for power loss reduction and voltage improvement: a new methodology

For compensating reactive power, shunt capacitors are often installed in electrical distribution networks. Consequently, in such systems, power loss reduces, voltage profile improves and feeder capacity releases. However, finding optimal size and location of capacitors in distribution networks is a complex combinatorial optimisation problem. In such problem, an objective function which is usually defined based on power losses and capacitor installation costs should be minimised subject to operational limitations. In this study, a newly developed metaheuristic technique, named crow search algorithm (CSA), is proposed for finding the optimal placement of the capacitors in a distribution network. CSA is a population-based technique inspired by the greedy behaviour of crows in finding better food sources. The main reasons of using CSA are its easy implementation, few parameters to adjust, fast convergence speed and high efficiency. In the case studies, simulated results indicate that the proposed CSA produces more accurate results than the other studied search methods.

Optimal capacitor placement in distribution systems for power loss reduction and voltage profile improvement

This study presents a two-stage procedure to identify the optimal locations and sizes of capacitors in radial distribution systems. In first stage, the loss sensitivity analysis using two loss sensitivity indices (LSIs) is employed to select the most candidate capacitors locations. In second stage, the ant colony optimisation algorithm is investigated to find the optimal locations and sizes of capacitors considering the minimisation of energy loss and capacitor costs as objective functions while system constraints are fully achieved. The fixed, practical switched and the combination of fixed and switched capacitors are considered to find the optimal solution. The backward/forward sweep algorithm is developed for the load flow calculations. The proposed procedure is applied to different standard test systems as 34-bus and 85-bus radial distribution systems. In addition, the application of the proposed procedure on a real distribution system of the East Delta Network as a part of the Unified Egyptian Network is used as a test system. Numerical results show the capability of the proposed procedure to find the optimal solution for significant saving in the total cost with more accurate and efficient, competitive compared with other methods in the literature especially with increasing the distribution system sizing.

A fuzzy discrete harmony search algorithm applied to annual cost reduction in radial distribution systems

Similarly to other optimization algorithms, harmony search (HS) is quite sensitive to the tuning parameters. Several variants of the HS algorithm have been developed to decrease the parameter-dependency character of HS. This article proposes a novel version of the discrete harmony search (DHS) algorithm, namely fuzzy discrete harmony search (FDHS), for optimizing capacitor placement in distribution systems. In the FDHS, a fuzzy system is employed to dynamically adjust two parameter values, i.e. harmony memory considering rate and pitch adjusting rate, with respect to normalized mean fitness of the harmony memory. The key aspect of FDHS is that it needs substantially fewer iterations to reach convergence in comparison with classical discrete harmony search (CDHS). To the authors’ knowledge, this is the first application of DHS to specify appropriate capacitor locations and their best amounts in the distribution systems. Simulations are provided for 10-, 34-, 85- and 141-bus distribution systems using CDHS and FDHS. The results show the effectiveness of FDHS over previous related studies.

Cuckoo Search Algorithm in Loss Minimization via Capacitor Placement in Distribution System

Improper placement of capacitor as one of the compensating devices will lead to under-compensation or over-compensation which may lead to possible monetary losses. Thus optimization process has become a priori to address this problem. This paper presents cuckoo search algorithm in loss minimization via capacitor placement in distribution system. Implementation of sensitivity analysis for location identification; followed by optimal sizing determination via cuckoo search is a remarkable effort for the compensating scheme. Validation on a reliability test model, namely the IEEE 33-bus radial distribution system has indicated promising results. With the development of optimization engine, an attempt to assess its feasibility can be done through the implementation on larger test system. This is demonstrated by the simulation results, which revealed that cuckoo is feasible in ensuring loss has been minimized while maintaining voltage level within the acceptable range

Development of a novel algorithm for optimal capacitor placement in distribution systems

Abstract Optimal capacitor placement in distribution systems solved by the hybrid method of CODEQ (called HCODEQ method) is proposed in this work. The concepts of chaotic search, opposition-based learning, and quantum mechanics are used in the CODEQ method to overcome the drawback of parameters selection in the differential evolution (DE). However, a larger population size must be used in the CODEQ method. That is a drawback for all evolutionary algorithms (EAs). To overcome this drawback, acceleration operation and migrating operation are embedded into the CODEQ method, i.e. HCODEQ method. The use of these two operations can increase the convergence speed without decreasing the diversity among individuals. One benchmark function and various-scale capacitor placement systems are used to compare the performance of the proposed method, CODEQ method, DE, simulated annealing (SA), and ant system (AS). Numerical results show that the performance of the HCODEQ method is better than the other methods.

Network Reconfiguration and Capacitor Placement in Distribution System with Harmonic Search Algorithm

This paper presents a recently developed approach Harmonic Search Algorithm for optimal reconfiguration and capacitor placement which is successfully applied to optimize radial distribution system with objective of reduction in the power loss for dynamic load. Simulation is carried out on Standard IEEE 33 bus distribution system. Results are compared with popular methods available in the literature like Genetic Algorithm and Ant Colony Optimization. Results show that the proposed algorithm can converge to optimum solution quickly with better accuracy when compare to Genetic Algorithm and Ant Colony Optimization.

A Novel Evolutionary Algorithm for Capacitor Placement in Distribution Systems

AbstractThis paper uses an effective method, CODEQ method, with integer programming for solving the capacitor placement problems in distribution systems. Different from the original differential evolution (DE), the concepts of chaotic search, opposition-based learning, and quantum mechanics are used in the CODEQ method to overcome the drawback of selection of the crossover factor and scaling factor used in the original DE method. One benchmark function and one 9-bus system from the literature are used to compare the performance of the CODEQ method with the DE, and simulated annealing (SA). Numerical results show that the performance of the CODEQ method is better than the other methods. Also, the CODEQ method used in 9-bus system is superior to some other methods in terms of solution power loss and costs.

A Novel Evolutionary Algorithm for Capacitor Placement in Distribution Systems

A Novel Evolutionary Algorithm for Capacitor Placement in Distribution Systems

Optimum shunt capacitor placement in distribution system—A review and comparative study

Shunt capacitors are commonly used in distribution system for reactive power compensation. Different analytical, numerical programming, heuristic and artificial intelligent based techniques have been proposed in the literature for optimum shunt capacitor bank (SCB) placement. This paper will present a very detailed overview of optimum SCB placement techniques. Six different approaches of optimum SCB placement based on minimization of power losses, weakest voltage bus approach and maximization of system loadability will be applied on four different radial distribution test systems. The results will be compared on the basis of power loss reduction, voltage profile improvement, system loadability maximization and the line limit constraint.

Energy Loss Reduction by Conductor Replacement and Capacitor Placement in Distribution Systems

Traditionally, capacitor placement and conductor replacement have been considered as independent solutions for loss reduction in distribution networks. However, these two methods have an inherent coupling relationship, especially at harmonic frequencies. This paper presents a joint optimization algorithm for both conductor replacement of overhead lines and capacitor placement to minimize energy losses in the presence of harmonics throughout the distribution system, such that both individual and total harmonic distortion of bus voltages are kept within the acceptable levels. All actual conditions including time varying nature of loads, network extension over the planning horizon, annual load growth and different load patterns are taken into account based on the realistic data. By applying the proposed method, the economic cost and energy losses are remarkably reduced compared to that could be achieved by applying these two methods separately in the presence of harmonics. The proposed method is applied on a realistic distribution network of Sirjan city-center in Iran.

Optimal Capacitor Placement for Loss Reduction in Radial Distribution Feeder

A distribution system is an interface between the bulk power transmission system and the consumer. Among these systems, radial distribution system is popular because of low cost and simple design. In radial distribution feeders, the voltage at buses reduces and loss increases as moved away from the substation due to insufficient amount of reactive power. The reactive power requirement is provided by the shunt capacitor banks. The most important benefit of capacitor placement is loss reduction, voltage profile improvement, increment of power factor and freeing up the power system capacity. Optimal capacitor placement in distribution systems has been studied for a long time. It is an optimization problem which has an objective to define the optimal sizes and allocations of capacitors to be installed. This paper presents an approach for optimal capacitor banks placement in radial distribution feeders for loss reducction.

Optimal capacitor placement in distribution networks using Genetic Algorithm

One of the on-going studies in the power distribution system is optimal placement of capacitors to which designers pay attention since many years ago. The most important benefit of capacitor placement is loss reduction, voltage profi le improvement, increment of power factor and freeing up the power system capacity. This paper presents a new approach for capacitor allocation in a sample distribution system. The problem formulation considers most of effective parameters in the capacitorinstallation. One of the distinguished characteristics of the implementation of the Genetic Algorithm for optimal capacitor placement in distribution system is its multifunction capability. The proposed method on capacitor placement and detecting optimumcapacitance has been implemented and tested in a 9 -bus IEEE sample network in DIGSILENT and MATLAB environments.

Strategic capacitor placement in distribution systems by minimisation of harmonics amplification because of resonance

The capacitor placement problem (CPP) has been widely studied throughout the years. However, traditional methodologies either do not consider non-linear loads in the formulations or are highly dependent on the spectrum of the harmonic currents. Therefore the traditional methodologies have become unsuitable for distribution system planning studies. The proposed approach formulates the CPP as a multi-objective optimisation model while including economic and technical aspects in the minimisation process. An additional objective function introduces a quadratic minimisation of the voltage harmonic distortions produced by the harmonic currents drawn by non-linear loads according to the IEEE Std. 519-1992 limits. A new constraint based on a resonance index (RI) is also introduced as a form to extend the capacitors- lifetime. Furthermore, an aging model of capacitor dielectric insulation under a non-sinusoidal waveform scenario is used to estimate the expected real lifetime of capacitors. The proposed methodology was exhaustively tested on a 69-bus system and the results show that the methodology is adequate for planning capacitors and eliminates the need to focus in great detail on harmonic system data.

Efficient heuristic algorithm used for optimal capacitor placement in distribution systems

An efficient heuristic algorithm is presented in this work in order to solve the optimal capacitor placement problem in radial distribution systems. The proposal uses the solution from the mathematical model after relaxing the integrality of the discrete variables as a strategy to identify the most attractive bus to add capacitors to each step of the heuristic algorithm. The relaxed mathematical model is a non-linear programming problem and is solved using a specialized interior point method. The algorithm still incorporates an additional strategy of local search that enables the finding of a group of quality solutions after small alterations in the optimization strategy. Proposed solution methodology has been implemented and tested in known electric systems getting a satisfactory outcome compared with metaheuristic methods. The tests carried out in electric systems known in specialized literature reveal the satisfactory outcome of the proposed algorithm compared with metaheuristic methods.

Discrete Particle Swarm Optimization to Network Reconfiguration for Loss Reduction and Load Balancing

Particle swarm optimization (PSO) has emerged as a useful optimization tool for handling non-linear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness. This method has been applied successfully on some benchmark mathematical problems. A few PSO applications have been reported on real-world problems, such as network reconfiguration for loss reduction, load balancing, and even capacitor placement in distribution systems being discrete in nature. PSO is modified to discrete particle swarm optimization (DPSO). The results of DPSO are compared with the results of the genetic algorithm.