A Novel Quasi-opposition Based Sine Cosine Algorithm for Optimal Allocation and Sizing of Capacitor in Radial Distribution Systems

2021 ◽  
Author(s):  
Saubhagya Ranjan Biswal ◽  
GAURI SHANKAR
Keyword(s):  
Radial Distribution ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Search Space ◽  
Variable Load ◽  
Sensitivity Index ◽  
Optimization Approach ◽  
Capacitor Placement ◽  
Sine Cosine Algorithm ◽  
Benchmark Test Functions

Abstract Increasing trend in load demand has introduced many problems in distribution systems like more line losses, low power factor, voltage fluctuations and so on. These issues have become a vital challenge for the power utilities to resolve and maintain the system under healthy conditions. For handling these issues, optimal capacitor placement (OCP) in radial distribution systems employing an optimization approach is explored in this work. The present work proposes a novel application of quasi-opposition based sine cosine algorithm for solving OCP problem. The effectiveness and superiority of the proposed algorithm is verified over other algorithms using different standard benchmark test functions. For solving OCP problem, at first, the most deserving candidate buses for the OCP are identified using a new proposed sensitivity index that helps in reducing search space for the optimization process. Thereafter, by minimizing the losses and maximizing the net annual profit of the system, the optimal location and selection of the fixed-step capacitor banks are obtained. The efficacy of the proposed algorithm has been verified by comparing the results obtained with that of other state-of-the-art algorithms on the standard IEEE 85 bus and 118 bus radial distribution test systems considering full load and variable load scenarios.

Capacitor Placement in Radial Distribution System Using Oppositional Cuckoo Optimization Algorithm

2018 ◽  
Vol 9 (3) ◽  
pp. 64-95 ◽  
Author(s):  
Sneha Sultana ◽  
Provas Kumar Roy
Keyword(s):  
Radial Distribution ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Planning Problem ◽  
Radial Distribution System ◽  
Cuckoo Optimization Algorithm ◽  
Capacitor Placement

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.

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

2020 ◽  
Vol 10 (4) ◽  
pp. 1384
Author(s):  
Rabea Jamil Mahfoud ◽  
Nizar Faisal Alkayem ◽  
Yonghui Sun ◽  
Hassan Haes Alhelou ◽  
Pierluigi Siano ◽  
...  
Keyword(s):  
Decision Making ◽  
Differential Evolution ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Search Space ◽  
Initial Population ◽  
Optimal Planning ◽  
Sine Cosine Algorithm ◽  
Shunt Capacitors ◽  
Operational Constraints

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.

scholarly journals Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique

2021 ◽  
Vol 13 (12) ◽  
pp. 6644
Author(s):  
Ali Selim ◽  
Salah Kamel ◽  
Amal A. Mohamed ◽  
Ehab E. Elattar
Keyword(s):  
Power System ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Optimization Technique ◽  
Mathematical Formulation ◽  
Optimization Techniques ◽  
Sensitivity Factor ◽  
Hybrid Technique ◽  
Analytical Technique

In recent years, the integration of distributed generators (DGs) in radial distribution systems (RDS) has received considerable attention in power system research. The major purpose of DG integration is to decrease the power losses and improve the voltage profiles that directly lead to improving the overall efficiency of the power system. Therefore, this paper proposes a hybrid optimization technique based on analytical and metaheuristic algorithms for optimal DG allocation in RDS. In the proposed technique, the loss sensitivity factor (LSF) is utilized to reduce the search space of the DG locations, while the analytical technique is used to calculate initial DG sizes based on a mathematical formulation. Then, a metaheuristic sine cosine algorithm (SCA) is applied to identify the optimal DG allocation based on the LSF and analytical techniques instead of using random initialization. To prove the superiority and high performance of the proposed hybrid technique, two standard RDSs, IEEE 33-bus and 69-bus, are considered. Additionally, a comparison between the proposed techniques, standard SCA, and other existing optimization techniques is carried out. The main findings confirmed the enhancement in the convergence of the proposed technique compared with the standard SCA and the ability to allocate multiple DGs in RDS.

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