Study On Optimal Capacity Allocation Of Standalone Wind/Solar/Battery Hybrid Power System

The increasing energy crisis has become a main factor that restricts thedevelopment of the society. The development of new energy sources attracts more andmore people’s attention. The standalone wind/solar/battery hybrid power system,making full use of the nature complementary of wind and solar and improving thereliability of wind power generation and solar power generation separately, has abroad application prospect among the development of new energy technologies.The capacity of the hybrid power system needs to be optimised in order to tradeoff between power reliability and cost. Under the premise of meeting the reliability,try best to save the investment and improve the economy. In this paper, the workingprinciple of each part of the standalone wind/solar/battery hybrid power system iscompletely analysed. The mathematical models of wind turbine, photovoltaic paneland battery are established. An objective function combining Total Owning Cost andLoss of Power Supply Probability is built to keep a balance between the economy andreliability of the system. To solve the hybrid power system’s problems such as thenonlinearity, the complexity and huge computation, an improved particle swarmoptimisation algorithm is used in this paper, which integrates the taboo list to broadenthe search range and also introduces "restart "and" disturbance "operation to enhancethe global searching capability.Take Tianjin as an example. According to the wind speed, radiation and otherclimate conditions of Tianjin area and taking the living electricity consumption of100residents as the load, Use standard PSO algorithm and improved PSO algorithm inthis paper with20,50,100,1000,5000times iterations separately to calculate theoptimal capacity allocation of the standalone wind/solar/battery hybrid power system.Simulation examples show that the proposed algorithm has a more stable capability tofind the optimal solution in solving the capacity allocation of the standalonewind/solar/battery hybrid power system than the standard particle swarm optimizationalgorithm. Especially in the case that the number of iterations is small, improvedparticle swarm optimization algorithm is far more stable than the standard particleswarm optimization algorithm, while in the case that the number of iterations is large, the improved PSO algorithm can to be able to give a more optimized solution than thestandard particle swarm optimization algorithm. The improved particle swarmalgorithm optimization can find a better solution.