Capacitors In Radial Distribution Systems Research Articles

Optimal Location of Capacitor in a Radial Distribution System Using New Hybrid Method

This paper solves the problem of optimal sizing and locations of capacitors in radial distribution system using a new hybrid method combining a new stability index and a genetic algorithm to improve the loss, voltage and stability planes. The Bus Voltage Stability Index BVSI is used to determine the locations and the genetic algorithm GA to calculate the size. The GA-BVSI analytical-metaheuristic method, compared with existing methods, is more suitable and recommended for operators who are faced with the problem of sizing capacitors to improve the technical performance of their network. Keywords: Optimal sizing and locations; Capacitors; Radial distribution system; New stability index;Hybrid method.

Placement and Sizing of Distributed Generations and Shunt Capacitors in Radial Distribution Systems Using Hybrid Optimization Technique

This article presents a hybrid method based on analytical and metaheuristic optimization techniques for the optimal placement of distributed generations (DGs) and shunt capacitors (SCs) into radial distribution systems (RDSs) to minimize power loss. In the hybrid method, a meta-heuristic called the Salp Swarm Algorithm is utilized to determine the optimal locations of DGs and SCs, while an efficient analytical technique is applied to calculate the optimal sizes. To check the robustness of the proposed method, two standard IEEE systems are employed; IEEE 33-bus and 69-bus, and compared with existing optimization techniques. Also to confirm the ability of the proposed method on improving performance, it applied to an actual 94-bus Portuguese RDS. The obtained results show the feasibility of the proposed method in optimal allocating of the DG and SC into RDS.

A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity

Recently, the integration of distributed generators (DGs) in radial distribution systems (RDS) has been widely evolving due to its sustainability and lack of pollution. This study presents an efficient optimization technique named the honey badger algorithm (HBA) for specifying the optimum size and location of capacitors and different types of DGs to minimize the total active power loss of the network. The Combined Power Loss Sensitivity (CPLS) factor is deployed with the HBA to accelerate the estimation process by specifying the candidate buses for optimal placement of DGs and capacitors in RDS. The performance of the optimization algorithm is demonstrated through the application to the IEEE 69-bus standard RDS with different scenarios: DG Type-I, DG Type-III, and capacitor banks (CBs). Furthermore, the effects of simultaneously integrating single and multiple DG Type-I with DG Type-III are illustrated. The results obtained revealed the effectiveness of the HBA for optimizing the size and location of single and multiple DGs and CBs with a considerable decline in the system’s real power losses. Additionally, the results have been compared with those obtained by other known algorithms.

Optimal Placement of Capacitors in Radial Distribution Systems for Reducing Energy Loss

Optimal Placement of Capacitors in Radial Distribution Systems for Reducing Energy Loss

Optimal Allocation of DG and Capacitor in Distribution Networks Using a Novel Hybrid MFO-SCA Method

This paper proposes a novel hybrid (MFO-SCA) method based on Moth Flame Optimization (MFO) algorithm and Sine Cosine Algorithm (SCA). MFO is utilized for the exploitation phase while SCA is used for the exploration phase. In addition, the hybrid MFO-SCA method is used with combined power loss sensitivity (CPLS) to determine the optimal allocation of single and multiple of distributed generations (DGs) and capacitors in distribution system. In this paper, the total active power loss is used as a single objective function for incorporating DGs and capacitors in RDS. Also, this paper studies the system performance when integrating DGs or capacitors alone and DGs with capacitors simultaneously in RDS. The proposed method is validated using the standard IEEE 69-bus and IEEE 33-bus radial distribution system (RDS). From comparative study, the novel hybrid MFO-SCA proved its effectiveness in obtaining the best global optimum results of the objective function compared with other recent optimization techniques, especially SCA and MFO algorithms.

Optimal Placement and Sizing of Capacitors in Radial Distribution Systems: A Two-Stage Method

Optimal allocation of shunt capacitors in the radial distribution networks results in both technical and economic benefits. This paper presents a two-stage method of Loss Sensitivity Factor (LSF) and Cuckoo Search Algorithm (CSA) to find the optimal size and location of shunt capacitors with the objective of minimizing cost due to power loss and reactive power compensation of the distribution networks.
 The first stage utilizes the LSF to predict the potential candidate buses for shunt capacitor placement thereby reducing the search space of the second stage and avoiding unnecessary repetitive load flow while the second stage uses the CSA to find the size and actual placement of the shunt capacitors satisfying the operating constraints.
 The applicability of the proposed two stage method is tested on the standard IEEE 33-bus and Ayepe 34-bus Nigerian radial distribution networks of the Ibadan Electricity Distribution Company. After running the algorithm, the simulation results gave percentage real and reactive power loss reduction of 34.28% and 28.94% as compared to the base case for the IEEE 33-bus system while the percentage real and reactive power loss reduction of 22.89% and 21.40% was recorded for the Ayepe 34-bus system.
 Comparison of the obtained results with other techniques in literatures for the standardized IEEE 33-bus reveals the efficiency of the proposed method as it achieved technical benefits of reduced total power loss, improved voltage profile and bus voltage stability, and the economic benefit of reduced total cost due to electrical power loss and compensation.

Optimal Placement and Sizing of Inverter-Based Distributed Generation Units and Shunt Capacitors in Distorted Distribution Systems Using a Hybrid Phasor Particle Swarm Optimization and Gravitational Search Algorithm

In this paper, a novel hybrid population-based meta-heuristic algorithm, called the hybrid Phasor Particle Swarm Optimization and Gravitational Search Algorithm (PPSOGSA), is proposed to solve the problem of optimal placement and sizing of inverter-based distributed generation (DG) units and shunt capacitors in radial distribution systems with linear and non-linear loads. The objective of the problem is reduction of active power losses considering constraints of the fundamental frequency active and reactive power balance, RMS voltage, and total harmonic distortion of voltage (THDV) at each bus of the network, as well as the branch flow constraints. The performance of the PPSOGSA-based approach is evaluated on the standard IEEE 33- and 69-bus test systems under sinusoidal and non-sinusoidal operating conditions. Compared to the original PPSO and GSA and other algorithms commonly used in the optimal sitting and sizing problem of DG units and shunt capacitors, it is found that the proposed algorithm has yielded better results.

Optimal Placement and Sizing of Shunt Capacitors in Radial Distribution System Using Polar Bear Optimization Algorithm

Reduction in power loss while maintaining the acceptable voltage profile has become a challenge for distribution system operators due to expanded living standards. Properly sized shunt capacitors (SCs) allocated at suitable locations of the distribution system can enhance its performance by tackling the power quality issues and foster multiple technical and economic benefits. Most of the existing research work in this domain is accomplished at fixed loading conditions without incorporating purchasing, installation, operation and degradation costs of the SCs. In this work, an intelligent metaheuristic polar bear optimization algorithm (PBOA) is applied to solve the optimal capacitor placement and sizing problem in the radial distribution system (RDS) at various loading conditions. By formulating multiple objective functions for the annual operating cost (AOC), this work incorporates the cost of real power loss ( $$ P_{\text{loss}} $$ ) and various costs associated with SCs. The proposed technique is tested on various IEEE standard bus systems under different loading conditions. The proposed PBOA reduces AOC and $$ P_{\text{loss}} $$ of RDS while maintaining tolerable voltages at systems’ buses. The reductions of 51%, 35%, 26% and 53% in $$ P_{\text{loss}} $$ are observed for IEEE standard 15-, 33-, 34- and 85-bus systems, respectively, at 100% loading from their uncompensated cases. Similarly, reductions in AOCs for the same systems at 100% loading are 32%, 25%, 16% and 45%, respectively. These results prove superiority of proposed method over recent state-of-the-art algorithmic approaches. The results of this work can be useful for distribution system operators in achieving reliable and efficient operation of the power grid.

An enhanced sitting–sizing scheme for shunt capacitors in radial distribution systems using improved atom search optimization

In this paper, an enhanced sitting–sizing scheme for shunt capacitors (4SCs) in a radial distribution system (RDS) based on an improved atom search optimization (IASO) algorithm is proposed. IASO emulates the model of atomic motion in nature based on interaction forces among atoms. The main goal of the 4SCs problem is to reduce the line losses and minimize the capacitor installation cost by searching for the optimal location and sizing of the capacitors. This leads to improvements in the voltage profile and reliability of the system. The IASO algorithm is introduced to achieve the optimal sitting and sizing of capacitors for RDSs. The proposed IASO algorithm is benchmarked and validated on different radial systems, including the IEEE 33-bus, IEEE 34-bus, IEEE 65-bus, IEEE 85-bus and Marsa Matrouh networks, to demonstrate its performance in real-world applications. The results obtained by the proposed IASO algorithm are compared with the standard ASO, PSO, SCA, GWO and SSA algorithms. Furthermore, the significance of the obtained results is confirmed by performing a nonparametric statistical test, i.e., the Wilcoxon’s rank-sum at the 5% significance level. The comprehensive results demonstrate that the results obtained by the proposed IASO algorithm denominate the results obtained by the other algorithms and that IASO minimizes the operating costs while achieving better voltage profiles.

Improved Hybridization of Evolutionary Algorithms with a Sensitivity-Based Decision-Making Technique for the Optimal Planning of Shunt Capacitors in Radial Distribution Systems

In this paper, an improved hybridization of an evolutionary algorithm, named permutated oppositional differential evolution sine cosine algorithm (PODESCA) and also a sensitivity-based decision-making technique (SBDMT) are proposed to tackle the optimal planning of shunt capacitors (OPSC) problem in different-scale radial distribution systems (RDSs). The evolved PODESCA uniquely utilizes the mechanisms of differential evolution (DE) and an enhanced sine–cosine algorithm (SCA) to constitute the algorithm’s main structure. In addition, quasi-oppositional technique (QOT) is applied at the initialization stage to generate the initial population, and also inside the main loop. PODESCA is implemented to solve the OPSC problem, where the objective is to minimize the system’s total cost with the presence of capacitors subject to different operational constraints. Moreover, SBDMT is developed by using a multi-criteria decision-making (MCDM) approach; namely the technique for the order of preference by similarity to ideal solution (TOPSIS). By applying this approach, four sensitivity-based indices (SBIs) are set as inputs of TOPSIS, whereas the output is the highest potential buses for SC placement. Consequently, the OPSC problem’s search space is extensively and effectively reduced. Hence, based on the reduced search space, PODESCA is reimplemented on the OPSC problem, and the obtained results with and without reducing the search space by the proposed SBDMT are then compared. For further validation of the proposed methods, three RDSs are used, and then the results are compared with different methods from the literature. The performed comparisons demonstrate that the proposed methods overcome several previous methods and they are recommended as effective and robust techniques for solving the OPSC problem.

Optimal placement of multi-period-based switched capacitor in radial distribution systems

This paper proposes a methodology for optimal allocation of multi-period-based switchable capacitor in radial distribution systems to minimize the energy loss and improve the voltage profile. In the proposed methodology, each monthly typical day is divided to numerous time segments under a so-called number of segments (NOS) factor. Several possible values of NOS are evaluated to seek its impact on system's yearly loss. In the optimization process, by considering a common value of NOS, an optimal candidate bus for locating capacitor is obtained while the capacitor step is optimized in each segment. To speed up the solving process, a technical constraint is offered to ignore the non-important states for capacitor size evaluation. Moreover, two methods for load flow calculations including the direct load flow and backward/forward sweep methods are investigated. The proposed methodology is applied to IEEE 10-bus, 33-bus, 69-bus, and 85-bus systems, and thereby relevant conclusions are drawn.

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system performance. In this line, this paper proposes an enhanced genetic algorithm (EGA) that combines the merits of genetic algorithm and local search to find the optimal placement and capacity of the simultaneous allocation of DGs/SCs in the radial systems. Incorporating local search scheme enhances the search space capability and increases the exploration rate for finding the global solution. The proposed procedure aims at minimizing both total real power losses and the total voltage deviation in order to enhance the distribution system performance. To prove the proposed algorithm ability and scalability, three standard test systems, IEEE 33 bus, 69 bus, and 119-bus test distribution networks, are considered. The simulation results show that the proposed EGA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literature. Moreover, an economic based cost analysis is provided for light, shoulder and heavy loading levels. It was proven, the proposed EGA leads to significant improvements in the technical and economic points of view.

Simultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty

The rapid growth in load demand results in higher line loses in distribution systems and also demands distribution system augmentation. Apart from this, due to fluctuating loads, it becomes a challenge for the utility sectors to maintain voltage stability of the system under healthy condition. For addressing such problems, simultaneous optimal placement of distributed generations (DGs) and capacitors in radial distribution systems employing multi-objective optimisation technique based approach is explored in this work. In line with this, the present work uses a simple and powerful multi-objective strength Pareto evolutionary algorithm 2 (SPEA2) for solving distributed generator and capacitor placement problem considering load uncertainty. The uncertainty characteristics of load are designed by probabilistic approach and the same is utilised during the optimisation process. Thereafter, a set of non-dominated Pareto optimal solution is obtained according to the objective function value. A compromised solution is selected from the set of Pareto optimal solutions by using fuzzy set theory. Along with the above, the impact of reverse power flow is studied by taking different test cases. The studied algorithm has been tested on different standard IEEE 33-bus and 69-bus radial distribution test systems.

A Review of Cuckoo Search Algorithm Based Optimal Siting and Sizing of Shunt Capacitors in Radial Distribution Systems

Compensating reactive power deficiency on power grids is a central concern in the distribution of energy management systems. Several approaches have been adopted over time to minimize the total real power loss and enhancing bus voltage profile. Shunt capacitor has been used from time immemorial for addressing issue of reactive power compensation at the distribution end of power systems, and the extent of benefits derivable from its usage depend solely on correct siting and sizing. To this effect, meta-heuristic algorithms are promising optimization tools for achieving these objectives. This paper, therefore, presents a comprehensive review of cuckoo search algorithm based on optimal siting and sizing of shunt capacitors in radial distribution systems. The suitability, in addition to strengths and weakness of each approaches reported in the reviewed articles have been painstakingly x-rayed. Based on the review, it was observed that a two-stage approach is always adopted in the compensation process: the pre-selection of potential or sensitive nodes and the optimal sizing of shunt capacitors needed for the compensation. For the pre-location, Voltage Stability Index and Loss Sensitivity Factor were found to be comparatively less complex and highly suitable techniques. Another cogent discovery from this review is that less attention has been drawn to the use of cuckoo search algorithm by Nigerian researchers. Therefore, regarding Nigerian electric grid system, the use of cuckoo search algorithm in reactive power support presents a research gap for further investigations.

Optimal Sizing and Placement of Capacitors in Radial Distribution Systems Based on Grey Wolf, Dragonfly and Moth–Flame Optimization Algorithms

The applications of grey wolf (GWO), dragonfly (DFO) and moth–flame (MFA) optimization techniques for optimum sitting of capacitors in various radial distribution systems (RDSs) are presented. The loss sensitivity factor is applied to determine the most candidate buses. Then, each optimization technique is utilized to find optimum placements and sizes of capacitors for determined Buses. In this study, 33-, 69- and 118-bus RDSs are considered for validating the effectiveness and efficiency of studied algorithms. The convergence performance is evaluated for tested RDSs using MATLAB/Simulink software. The obtained results confirm that GWO, DFO and MFA offer accurate convergence to the global minimum point of the objective function with high convergence speed. The ability of the studied techniques for enhancing voltage profiles with considered distribution systems is achieved. Finally, a comparison study between each studied technique with each other and with other techniques like PSO, fuzzy-GA, heuristic, DSA, TLBO, DA-PS, FPA and CSA has been carried out. The parameters of the comparison include: efficiency, execution time, the speed of convergence, minimizing total cost and increasing net savings. The results of comparison indicated that GWO-based algorithm has accurate convergence to optimal location and size of capacitor banks. In addition, it has the best performance in comparison with other techniques.

Capacitor Placement in Radial Distribution System Using Oppositional Cuckoo Optimization Algorithm

Capacitors in distribution systems are used to supply reactive power to minimize power loss. This article presents an efficient optimization algorithm named oppositional cuckoo optimization algorithm (OCOA) for optimal allocation of capacitor in radial distribution systems to determine the optimal locations and sizes of capacitors with an objective of reduction of total cost considering different constraints. To test feasibility and effectiveness of the proposed OCOA, it is applied on 22-bus, 69-bus, 85-bus and 141-bus radial distribution systems as test studies and the results are compared with other methods available in literature. Comparison between the proposed method in this article and similar methods in other research works shows the effectiveness of the proposed method for solving optimum capacitor planning problem in radial distribution system.

A Novel Analytical Technique for Optimal Allocation of Capacitors in Radial Distribution Systems

In this paper, a novel analytical technique is proposed to determine the optimal size and location of shunt capacitor units in radial distribution systems. An objective function is formulated to reduce real power loss, to improve thevoltage profile and to increase annual cost savings. A new constant, the Loss Sensitivity Constant (LSC), is proposed here. The value of LSC decides the location and size of candidate buses. The technique is demonstrated on an IEEE-33 bus system at different load levels and the 130-bus distribution system of Jamawa Ramgarh village, Jaipur city. The obtained results are compared with the latest optimization techniques to show the effectiveness and robustness of the proposed technique.

Multiobjective hybrid evolutionary approach for optimal planning of shunt capacitors in radial distribution systems with load models

Abstract This article proposes a novel hybrid heuristic search algorithm based on Harmony search and particle artificial bee colony algorithm (HSA-PABC) for shunt capacitor placement problem. The objective function is framed to minimize power loss and to maximize voltage stability. To search for the optimal location of shunt capacitors, the combinatorial use of loss sensitivity factor and hybrid HSA-PABC algorithm is utilized. In this paper, different types of voltage dependent load models are taken into consideration to investigate their influence on the active power loss and voltage stability of the RDN. Simulation results shows that the voltage dependent load models lead to completely different solutions interms of power loss reduction, voltage stability improvement and net annual savings which are the crucial parameters in the decision process of optimal shunt capacitor placement problem. The result outcomes of the proposed hybrid algorithm outperform the results of other heuristic techniques in the literature.

Оптимальное размещение батарей конденсаторов в радиальной распределительной сети

The increasing greatly demand leads to increase in system power losses and voltage profile disturbances. The need for more effective power distribution system has become more urgent. In this regards, shunt capacitors installation on radial distribution has always been an important research area to get the optimal allocations required for voltage profile improvement, system losses reduction and power factor correction. The developed study provides two-stages to evaluate the optimal allocation of capacitors in radial distribution system. In this paper, two stages are introduced. In the first stage, the loss sensitivity analysis with two methods is employed to select the most appropriate candidate capacitor placement. In the second stage, a novel hybrid particle swarm optimization (HPSO)algorithm is implemented to find optimal sizing and allocations of capacitors and their settings from the selected buses. The proposed algorithm has been tested on different test systems as 15-bus, and 34-bus IEEE standard radial distribution systems. Moreover, the proposed algorithm has been tested on different sizes of other radial distribution systems. In order to validate the proposed approach, the obtained results have been compared with other methods. The numerical results have been proved the capability of the proposed approach to find the optimal solutions with system losses reduction, voltage profile improvement and power factor correction. Numerical results have been evaluated by MATLAB package.

Optimal locations and sizing of capacitors in radial distribution systems using mine blast algorithm

In this paper, a mine blast algorithm (MBA) is proposed for optimal allocations and sizing of capacitors in various distribution systems. First, the most candidate buses for installing capacitors are suggested using loss sensitivity factors (LSF). Then, the proposed MBA is employed to deduce the size of capacitors and their locations from the elected buses. The objective function is designed to reduce the total cost and, consequently, to increase the net saving per year. The proposed algorithm is tested on 10 and 85 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight their benefits. Moreover, the results are introduced to verify the effectiveness of the suggested algorithm to minimize the losses and total cost and to enhance the voltage profile and net saving for various distribution systems and loading conditions.