Optimal sizing and placement of multiple renewable distribution generation and DSTATCOM in radial distribution systems using hybrid lightning search algorithm‐simplex method optimization algorithm

2020 ◽  
Author(s):  
Sakthi Gokul Rajan Chinnaraj ◽  
Ravi Kuppan
Keyword(s):  
Radial Distribution ◽  
Optimization Algorithm ◽  
Simplex Method ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Optimal Sizing ◽  
Method Optimization ◽  
Distribution Generation

scholarly journals Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-34 ◽  
Author(s):  
Thang Trung Nguyen ◽  
Thai Dinh Pham ◽  
Le Chi Kien ◽  
Le Van Dai
Keyword(s):  
Power Systems ◽  
Radial Distribution ◽  
Optimization Algorithm ◽  
Distribution Systems ◽  
Harmonic Distortion ◽  
Total Power ◽  
Solar Photovoltaic ◽  
Voltage Profile ◽  
Distribution Generation ◽  
The Impact

This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. In the considered problem, four single objectives consisting of total power losses, capacity of all PVDGUs, voltage profile index, and harmonic distortions are minimized independently while satisfying branch current limits, voltage limits, and harmonic distortion limits exactly and simultaneously. The performance of the proposed ICOA method has been improved significantly since two improvements were carried out on the two new solution generations of the conventional coyote optimization algorithm (COA). By finding four single objectives from two IEEE distribution power systems with 33 buses and 69 buses, the impact of each proposed improvement and two proposed improvements on the real performance of ICOA has been investigated. ICOA was superior to COA in terms of capability of finding higher quality solutions, more stable search ability, and faster convergence speed. Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. The result comparisons have also indicated the outstanding performance of ICOA because it could find much better results than these methods, especially SFO, SSA, and GA. Consequently, the proposed ICOA is a very effective method for finding the optimal location and capacity of PVDGUs in radial distribution power systems.

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.

Sign in / Sign up

Export Citation Format

Share Document