Optimal Coordination Of Wind-Solar-Thermal Combined Power System Based On Improved Particle Swarm

Since the 21 st century,the problems of environment and the lack of resource has become the main factor that restrict the development of power system.Traditional energy generation has could not meet the need of society,and clean energy has become an important method that can solve environmental and resource issues.With the large scale of solar energy and wind energy entering grid,the random fluctuation and instability will take definitely impact on the stability of power grid.Wind power and solar power generation technologies are relatively successful in today.Simultaneously,thermal power generation has the advantages of fast response and high stability.Wind power generation and solar power generation are complementary to a certain extent,meanwhile,thermal power generation can balance the random fluctuation of these two clean energy sources.Therefore,it is important to study on wind-solar-thermal combined power system(WPTCS).This paper proposes an economic scheduling model and an environment and spare capacity model about WPTCS.The models slove the problem of load fluctuation that be caused by the stochastic volatility and uncertainty of wind power and solar radiation.Using the improved particle swarm algorithm to simulate models,the simulation results show the models is effective.The main contents are:(1)Characteristics of the wind farm is described and deducing the probability distribution of wind speed.The characteristics and various parameters of photovoltaic power generation are also introduced in the paper.And it describes the burning and pollution characteristics of thermal power generation.The characteristics of WPTCS optimization scheduling are analyzed.All of these lay a theoretical foundation for joint scheduling.(2)Based on least squares support vector machine(LSSVM),a wavelet analysis and least squares support vector machine(WA-LSSVM)method is proposed for forecasting wind speed and solar radiation.And the results were compared with the actual results,which shows the prediction method is effective.The power of wind generation and solar photovoltaic generations was calculated.,which provides datas for WPTCS.(3)In order to meeting the increasing environmental sustainability requirement,an environmental and spare capacityscheduling model of WPTCS was proposed that basis on the economic mathematical model.This model takes c cost into account that caused by the random of wind power and solar photovoltaic power generation,and quantifying environmental cost.Minimizing the total of power generation cost of WPTCS.(4)An improved particle swarm optimization(IPSO)algorithm is proposed to simulate the economic mathematics model and the environment and spare capacity model of the WTSCS.The result showes the correctness of the two model.It solves the minimum value of the objective function and the load distribution during units within 24 hours.The results show the effectiveness of established models and IPSO.