Title :
Optimal capacity allocation of standalone wind/solar/battery hybrid power system based on improved particle swarm optimisation algorithm
Author :
Jidong Wang ; Fan Yang
Author_Institution :
Key Lab. of Smart Grid of Minist. of Educ., Tianjin Univ., Tianjin, China
Abstract :
A standalone wind/solar/battery hybrid power system, making full use of the nature complementarity between wind and solar energy, has an extensive application prospect among various newly developed energy technologies. The capacity of the hybrid power system needs to be optimised in order to make a tradeoff between power reliability and cost. In this study, each part of the wind/solar/battery hybrid power system is analysed in detail and an objective function combining total owning cost and loss of power supply probability is built. To solve the problems with non-linearity, complexity and huge computation, an improved particle swarm optimisation (PSO) algorithm is developed, which integrates the taboo list to broaden the search range and introduces `restart´ and `disturbance´ operation to enhance the global searching capability. The simulation results indicate that the proposed algorithm is more stable and provides better results in solving the optimal allocation of the capacity of the standalone wind/solar/battery hybrid power system compared with the standard PSO algorithm.
Keywords :
battery storage plants; hybrid power systems; particle swarm optimisation; power generation economics; power generation reliability; solar power stations; wind power plants; PSO algorithm; optimal capacity allocation; particle swarm optimisation algorithm; power cost; power reliability; power supply probability; solar energy; standalone wind-solar-battery hybrid power system; wind energy;
Journal_Title :
Renewable Power Generation, IET
DOI :
10.1049/iet-rpg.2012.0329