Research On "Source-Load-Storage" Optimal Dispatch Of Active Distribution Network

In today’s society,the application of clean and renewable energy is becoming more and more extensive,and the distribution network is constantly transforming and upgrading.With the gradual development of distributed power generation,the traditional unidirectional distribution network has gradually evolved into a bidirectional and complex active distribution network.In this process,the addition of distributed power sources such as photovoltaic power generation and wind power generation provides a huge impetus for the development of active distribution networks,but also brings new challenges to the distribution system.Realizing the optimal dispatch of distributed power generation,flexible load and energy storage system can improve the power supply reliability and dispatch economy of the power system,and establish a green power grid,which is very important to solve the problems caused by the randomness and volatility of distributed power.Therefore,how to solve this problem has become an important direction that needs to be focused on in the field of power systems.Based on this,this paper conducts in-depth research on the "source-load-storage" optimal dispatching of the active distribution network.The specific research contents are as follows:First of all,the research background and significance of this paper are proposed,and the research status of the coordinated dispatch between active distribution network and sourceload storage is analyzed at home and abroad,and the active resources of active distribution network are introduced in detail,including distributed power generation represented by wind and solar,flexible load classification,types of energy storage,and the basic theory of power flow calculation of active distribution network.Secondly,considering the increase in the penetration rate of urban electric vehicles and the greater impact of electric vehicle charging load on the power grid,energy storage as an emerging active distribution network resource can improve the stability and safety of the power system.This paper proposes a two-layer optimization method of active distribution network considering the interests of energy storage operators and electric vehicles,and uses time-of-use price guidance for lower electric vehicle users for dispatch optimization,and upper energy storage operators interact with the distribution network based on the lower dispatching data and their own conditions.Reduce the impact of electric vehicle charging on the power grid through dispatching,and reduce the peak-valley difference of load.At the same time,the genetic algorithm is integrated into the simulated annealing algorithm,and an improved simulated annealing algorithm is proposed,which improves the problem of easy loss of optimal solution of the simulated annealing algorithm,accelerates the convergence speed of the algorithm,improves the convergence accuracy of the algorithm,and uses the test function to verify the feasibility and superiority of the convergence of the algorithm.The improved simulated annealing algorithm is used to solve the two-layer optimization model of active distribution network,and the simulation is carried out by IEEE 33 node system,which verifies the effectiveness of the proposed model and method.Finally,considering the "source-load-storage" coordinated scheduling,an optimal dispatching model of "source-load-storage" of the active distribution network considering the uncertainty of distributed power and user response is proposed.In order to cope with the influence of distributed power fluctuation on power grid operation,a robust and optimized dispatching strategy for active distribution network aiming at the uncertainty of distributed power source is proposed.The concept of robust cost coefficient is proposed,and the impact of different volatility coefficients of distributed power supply on dispatching cost is studied by determining the robust cost coefficient.Aiming at the problem of user response uncertainty,this paper uses the forward cloud generator to generate multiple random scenarios,and uses the scenario reduction technology to reduce them,and transforms the load response uncertainty variables into deterministic variables in typical scenarios.A typical scenario with an 80% occurrence probability is selected for analysis,and three schemes are proposed for simulation analysis based on the selected scenario.The "source-load-storage" optimization scheduling model of the active distribution network proposed in this paper is verified by engineering examples,which promotes the consumption of distributed power sources and reduces the fluctuation of user response and the peak-valley difference of load.