Research On The Power Configuration Optimization And Economic Dispatch In Isolated Microgrid

The development and utilization of clean and renewable energy is beneficial to environmental protection and is also the inevitable choice to solve the increasingly serious energy problems.As a beneficial supplement to the main power grid,a microgrid system that includes various renewable energy sources such as wind turbines and photovoltaic array can not only make full use of renewable clean energy,but also solve power supply problems in remote areas,and improve the power supply stability of the power system.The application of microgrids is promising.This paper takes an isolated microgrid with wind turbines,photovoltaic array,diesel generators,and energy storage system as an example to conduct in-depth research on power supply configuration optimization and economic dispatch of microgrids.The main research contents are as follows:Considering the economy,reliability and environmental protection of an independent micro-grid system,an independent micro-grid multi-objective optimization model has been established.two commonly used micro-grid energy management strategies(static management strategies and dynamic management strategies)have been analyzed,aiming at their shortcomings,this paper proposes a dynamic management correction strategy.Dynamic management strategies and dynamic management correction strategies were adopted to compare the power optimization configuration results under the two strategies and the superiority of the dynamic management correction strategy in economy and reliability was verified.For the discrete domain optimization problem based on the improved non-dominated sorting genetic algorithm(NSGA2),a hybrid discretization method is proposed and the NSGA2 algorithm is used to solve the power optimization configuration model of the two power supply combinations “WT+PV+BESS+DE” and “WT+PV+DE”.The results show that configuring a certain-capacity energy storage system in an independent microgrid can improve the economical efficiency and reliability of the microgrid system.The commonly used wind power forecasting methods are analyzed,and the RBF neural network(HHDE-RBF)based on hybrid hierarchical differential evolution algorithm is proposed for wind power forecasting;The wind power forecasting flow based on HHDE-RBF neural network is designed.By the example of wind power forecasting,the HHDE-RBF neural network is compared with the existing RBF neural network based on the competitor penalty learning algorithm;The results show that the HHDE-RBF neural network is superior to the latter in wind power prediction accuracy and stability.The piecewise exponential distribution model with flexible shape and simple form is used to correct the wind power forecast error;the wind power forecast error correction process based on the segmented exponential distribution is designed.The wind power predicted values before and after the error correction are compared with the actual values,and the validity of the error correction based on the piecewise exponential distribution is verified.Taking the wind power data before and after the error correction as input,the simulation of the economic dispatch of the independent micro-grid is performed.The results show that the forecast error correction can reduce the adverse effect of the randomness of wind energy on the stability of the independent micro-grid system and improve the economical and reliable operation of the system.