Research On Stochastic Optimization Algorithm For Dynamic Economic Dispatch Of Power System With Correlated New Energy

Recently,with the continuous promotion of national energy policies and power system reforms,new energy such as wind power and solar energy have received increasing attention,and their speed and scale of development have continued to increase.On the one hand,the pollution and insufficient problem traditional energy faced are alleviated.On the other hand,the stochastic and correlation of new energy have brought great challenges to the dynamic economic dispatch(DED)of power systems.This paper models the correlation of new energy from the diversity and multidimensionality.Based on this,it studies the stochastic optimization algorithm for dynamic economic dispatch of power systems with correlated new energy.For the deficiencies of traditional correlation measurement,such as mapping method and regression analysis method,Copula function is proposed to model new energy correlation.The Copula function can not only capture the nonlinearity,asymmetry,and tail correlation between variables,but also can be used for multivariate distribution model and stochastic simulation.When describing the correlation,there is no limit to the edge distribution,and almost contains all correlated information of stochastic variables,makes the correlation description more perfect.On the level of new energy diversity,the wind-solar hybrid power generation system is the hot spot of current research.The correlation between wind energy and solar energy makes the power output more stable and reduces the stochastic.Therefore,this paper model the correlation of wind energy and solar energy based on the Copula function.The results show that there is a strong complementarity between wind energy and solar energy and should be taken into account in the economic dispatch.Based on the correlation index obtained from wind and solar complementarity modeling,the copularnd function is used to improve the scene generation steps of the scene method(SM)to obtain the wind-solar hybrid joint scene samples.And based on the probability distance,the scene is eliminated to obtain the error scene.In this way,the stochastic and complementary of new energy are taken into account in economic dispatching.Finally,a microgrid with high-permeability wind energy and solar energy is taken as an example,and the improved scene method is adopted to solve the power grid dynamic economic dispatch model considering wind-solar complementarity.Results verify the effectiveness of the proposed algorithm.On the level of new energy multidimensionality,large-scale wind power is currently connected to the power grid mostly in the form of multiple wind farms.Affected by climate and topography,there are correlation among wind farms within a certain area,so this paper describe the correlation of high-dimensional wind farms based on Copula function.For the long time-consuming in solving large-scale problems of the scene method,an improved two-stage compensation stochastic optimization algorithm is proposed to solve the dynamic economic dispatch problem of power grid considering the high-dimensional wind farms correlation.By the decoupling of conventional variables and stochastic variables,the drawbacks of “dimensional disasters” of traditional stochastic optimization methods are overcome.The calculation of the expected value of compensation cost is usually limited by the dimension of the correlated wind farms,and the direction of the iterative is not clear enough to lead the convergence.So the recursive dynamic multivariable linear regression method based on global least squares is introduced to improve the proposed algorithm.By dynamic updating of compensation penalty expectation,the solution of the two-stage model achieves fast convergence.The examples of IEEE118 system and a provincial actual power system verify the effectiveness of the proposed algorithm.