A Study On Smart Grid Dispatching Strategy Based On Classification Of Load Aggregators

The gradual maturity of smart grid technology has created gigantic development space for demand-side management and new energy utilization.However,after demand response participates in grid dispatching,it brings impacts and challenges to both the source and load of the smart grid.As a modern market entity,load aggregators can classify and aggregate small and medium-sized flexible loads to participate in the glamorous grid dispatching,in this way load aggregators can relieve the uncertainty of both sides of the source and load.How to study the characteristics of load aggregators to participate in smart grid dispatching is of great significance to the development of smart grids.This thesis focuses on the dispatching decision-making problem of wind energy smart grid with participation of load aggregators,and examines ways to combine load aggregator type to make scheduling decision under different participation methods,by analyzing the characteristics of load aggregator participation in dispatching from two aspects: how to load aggregators participate in dispatching and the types of load aggregators.The main research work of this dissertation is as follows:In the participation method in which the compensation price of the load aggregator is determined by the grid side,a smart grid integrated dispatch model including the grid-side operating cost,wind abandonment cost and load aggregator compensation cost is established.According to different types of aggregated loads,load aggregators are classified into commercial load aggregators and residential load aggregators,and different types of load aggregators participate in scheduling according to their own electricity consumption characteristics in time periods.Furthermore,in view of the fact that load aggregators aggregate a large number of small and medium-sized loads,they will have a certain default risk when participating in grid dispatching,proposing to evaluate the default level according to the ratio of the actual default amount of each aggregator to the total scalar amount of the load aggregator category,and carry out different levels of punishment mechanism,a hierarchical penalty rule for the classification of load aggregators has been established.Finally,the genetic algorithm with hybrid coding is used to solve the built model.The simulation example compares the scheduling results in three scenarios,which shows that the proposed method effectively increases the income of the power grid and load aggregators,also improves the utilization rate of wind energy.In the way that load aggregators compensate electricity prices by the market according to load demand pricing,a non-cooperative game mechanism for load aggregators classification based on the idea of the non-cooperative game is proposed.By establishing a multi-objective dispatching model that maximizes grid revenue and commercial load aggregators and residential load aggregators have the largest profits,various load aggregators can obtain the optimal bidding strategy in the competition.Finally,each load aggregator class determines the scheduling participation of each load aggregator according to the principle of proportional distribution.A multi-objective optimization algorithm is used to find a solution to the established optimization model.The simulation results of the calculation example select the solution that increases the revenue of both the grid size and the load aggregator from the obtained Pareto frontiers as the optimal solution,the results show the effectiveness of the proposed method.