Optimal placement of fixed and switched shunt capacitors for large-scale distribution systems using genetic algorithms

2010 ◽  
Author(s):  
Anil Swarnkar ◽  
Nikhil Gupta ◽  
K. R. Niazi
Keyword(s):  
Genetic Algorithms ◽  
Distribution Systems ◽  
Large Scale ◽  
Optimal Placement ◽  
Shunt Capacitors

scholarly journals Simultaneous Placement and Sizing of Distributed Generation Units and Shunt Capacitors on Radial Distribution Systems Using Cuckoo Search Algorithm

2021 ◽  
pp. 43-58
Author(s):  
Sunday Adeleke Salimon ◽  
Gafari Abiola Adepoju ◽  
Isaiah Gbadegesin Adebayo ◽  
Oluwadamilare Bode Adewuyi ◽  
Saheed Oluwasina Amuda
Keyword(s):  
Radial Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Search Algorithm ◽  
Stability Index ◽  
Cuckoo Search ◽  
Optimal Placement ◽  
Power Loss Reduction ◽  
Operational Test ◽  
Shunt Capacitors

This paper presents a Cuckoo Search (CS) algorithm-based methodology for simultaneous optimal placement and sizing of Shunt Capacitors (SCs) and Distributed Generations (DGs) together in radial distribution systems. The objectives of the work are to minimize the real power and reactive power losses while maximizing the voltage stability index of the distribution network subjected to equality and inequality constraints. Different operational test cases are considered namely installation of SCs only, DGs only, SCs before DGs, DGs before SCs, and SCs and DGs at one time. The proposed method has been demonstrated on standard IEEE 33-bus and a practical Ayepe 34-bus radial distribution test systems. The highest percentage power loss reduction of 94.4% and other substantial benefits are obtained when SCs and DGs are optimally installed simultaneously. Simulated results obtained from the proposed technique are compared with other well-known optimization algorithms and found to be more effective.

scholarly journals Optimal placement and sizing of shunt capacitors in distorted distribution systems using a hybrid algorithm

2021 ◽  
Vol 18 (1) ◽  
pp. 115-135
Author(s):  
Milos Milovanovic ◽  
Jordan Radosavljevic ◽  
Bojan Perovic
Keyword(s):  
Distribution Systems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Harmonic Distortion ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Total Annual Cost ◽  
Optimal Size ◽  
Market Simulation ◽  
Shunt Capacitors

In this paper, a novel hybrid phasor particle swarm optimization and gravitational search algorithm, namely the hybrid PPSOGSA algorithm, is proposed to find the optimal size and location of shunt capacitors in distribution systems with non-linear loads. The performance of PPSOGSA are studied and evaluated using the IEEE 9- and 85-bus test systems with the objective of minimizing the total annual cost of the system. The procedure is conducted taking into account effects of harmonic distortion and discrete size of capacitors available in the market. Simulation results are compared with those obtained by other optimization techniques, and verified using the Electrical Transient Analysis Program (ETAP). It was established that that the hybrid PPSOGSA algorithm provides better solutions in terms of convergence and accuracy.

scholarly journals Optimal Sizing and Placement of Capacitor Banks in Distribution Networks Using a Genetic Algorithm

Electricity ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 187-204
Author(s):  
Gian Giuseppe Soma
Keyword(s):  
Genetic Algorithm ◽  
Electricity Market ◽  
Distribution Systems ◽  
Reactive Power ◽  
Electricity Consumption ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Capacitor Banks ◽  
Control Pattern ◽  
Definition Of

Nowadays, response to electricity consumption growth is mainly supported by efficiency; therefore, this is the new main goal in the development of electric distribution networks, which must fully comply with the system’s constraints. In recent decades, the issue of independent reactive power services, including the optimal placement of capacitors in the grid due to the restructuring of the electricity industry and the creation of a competitive electricity market, has received attention from related companies. In this context, a genetic algorithm is proposed for optimal planning of capacitor banks. A case study derived from a real network, considering the application of suitable daily profiles for loads and generators, to obtain a better representation of the electrical conditions, is discussed in the present paper. The results confirmed that some placement solutions can be obtained with a good compromise between costs and benefits; the adopted benefits are energy losses and power factor infringements, taking into account the network technical limits. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of capacitor banks in distribution systems, with the definition of a suitable control pattern, have been proved.

scholarly journals A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

2021 ◽  
Vol 13 (6) ◽  
pp. 3308
Author(s):  
Chandrasekaran Venkatesan ◽  
Raju Kannadasan ◽  
Mohammed H. Alsharif ◽  
Mun-Kyeom Kim ◽  
Jamel Nebhen
Keyword(s):  
Multiobjective Optimization ◽  
Distributed Generation ◽  
Radial Distribution ◽  
Hybrid Method ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Optimal Placement ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Metaheuristic Optimization

Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB and DG injection in the RDS greatly depend on selecting a suitable number of CBs/DGs and their volume along with the finest location. This work proposes applying a hybrid enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) algorithm for optimal placement and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves. On the other hand, PSO is a swarm-based metaheuristic optimization algorithm that finds the optimal solution to a problem through the movement of the particles. The advantages of both techniques are utilized to acquire mutual benefits, i.e., the exploration ability of the EGWO and the exploitation ability of the PSO. The proposed hybrid method has a high convergence speed and is not trapped in local optimal. Using this hybrid method, technical, economic, and environmental advantages are enhanced using multiobjective functions (MOF) such as minimizing active power losses, voltage deviation index (VDI), the total cost of electrical energy, and total emissions from generation sources and enhancing the voltage stability index (VSI). Six different operational cases are considered and carried out on two standard distribution systems, namely, IEEE 33- and 69-bus RDSs, to demonstrate the proposed scheme’s effectiveness extensively. The simulated results are compared with existing optimization algorithms. From the obtained results, it is observed that the proposed EGWO-PSO gives distinguished enhancements in multiobjective optimization of different conflicting objective functions and high-level performance with global optimal values.

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