scholarly journals Optimal Design of Grid-Connected Solar Photovoltaic System Using Selective Particle Swarm Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Habtemariam Aberie Kefale ◽  
Elias Mandefro Getie ◽  
Kassaye Gizaw Eshetie

The electricity distribution network in Ethiopia has the radial nature of network configuration. The interruption of power is due to overloading and failure of distribution lines due to external forces, like trees, animals, and wind. The failure of the radial distribution network brings blackout in the whole power system network as there is no alternative electricity supply. The renewable energy potential of Bahir Dar, Ethiopia, especially solar power is abundant and needs a mechanism to give a response for electricity demand in the country and city other than expecting from the national grid. The solar photovoltaic system interconnection in radial feeders may bring a solution for power interruption and network performance. The sizing and siting of the solar photovoltaic system in the Ethiopian radial distribution system required an optimization tool to obtain better distribution network parameter. The power loss minimization and voltage profile enhancement of the radial distribution network are the key objectives of this research. Selective particle swarm optimization (SPSO) is used to fix the size and site of installation for network capacity enhancement. A multiobjective optimization problem is formulated so as to meet different constraints to be optimized by the SPSO. Finally, the SPSO enables determining proper size and site of solar power installation and bringing better performance in the radial distribution network of Ethiopia.

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2516
Author(s):  
Klemen Deželak ◽  
Peter Bracinik ◽  
Klemen Sredenšek ◽  
Sebastijan Seme

This paper deals with photovoltaic (PV) power plant modeling and its integration into the medium-voltage distribution network. Apart from solar cells, a simulation model includes a boost converter, voltage-oriented controller and LCL filter. The main emphasis is given to the comparison of two optimization methods—particle swarm optimization (PSO) and the Ziegler–Nichols (ZN) tuning method, approaches that are used for the parameters of Proportional-Integral (PI) controllers determination. A PI controller is commonly used because of its performance, but it is limited in its effectiveness if there is a change in the parameters of the system. In our case, the aforementioned change is caused by switching the feeders of the distribution network from an open-loop to a closed-loop arrangement. The simulation results have claimed the superiority of the PSO algorithm, while the classical ZN tuning method is acceptable in a limited area of operation.


Author(s):  
Jijun Liu ◽  
Yuxin Bai ◽  
Yingfeng He

This work aims at solving complex problems of the optimal scheduling model of active distribution network, teaching strategies are proposed to improve the global search ability of particle swarm optimization. Moreover, based on the improved Euclidean distance cyclic crowding sorting strategy, the convergence ability of Li Zhiquan algorithm is improved. With the cost and voltage indexes of the energy storage system of the distribution network as the goal, different optimized configuration schemes are constructed, and the improved HTL-MOPSO algorithm is adopted to find the solution. The results show that compared with the traditional TV-MOPSO algorithm, the proposed algorithm has better convergence performance and optimization ability, and has a lower economic cost. In short, the algorithm proposed can provide a basis for improving the optimization of active distribution network scheduling strategies.


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