Research On Distributionally Robust Scheduling Strategy Of Demand Side Resource Considering Uncertainty Of Response

In recent years,the development of society,the demand for low-carbon energy utilization and environmental protection is higher and higher,the proportion of new energy generation has been significantly increased.Because of its natural characteristic,the power output of new energy has great intermittence and volatility.So it is urgent to increase the auxiliary service resources such as peak regulation of power grid.With the further development of advanced measurement devices and advanced communication technology,more and more flexible users on the demand side will be able to participate in the market response.The demand response aggregator organically links the network side with the demand side,fully tap the potential of flexible adjustable load response,and provide a platform for small and medium capacity demand side flexible users to participate in the market.In this paper,the regulation and scheduling strategy of flexible load resource aggregation response is studied based on solving the problem of demand side flexible resource participating in market auxiliary service.The main work content and research results include the following aspects:1.The concept of demand response aggregator is introduced,and the interactive mode of demand response aggregator participating in the peak shaving service market is designed.The characteristics and module composition of the demand response aggregator are analyzed,and the way in which the flexible load participates in the peak shaving response is given.The interaction process between the demand response aggregator,the grid company and the end user is described.2.The modeling and solving methods of distributionally robust optimization methods to solve uncertainty problems are summarized.The construction methods of distribution set based on moment information,sub interval probability and probability distribution are introduced,and the general modeling process of various optimization models and their respective advantages and disadvantages are emphasized,the general algorithms for solving the distributionally robust optimization problems in power system are summarized.3.According to the specific characteristics of demand side flexible resources,in order to fully tap their schedulable potential,the uncertainty factors are analyzed,and the distributionally robust scheduling strategy of demand side resource considering uncertainty of response is proposed.Considering the uncertainty of response caused by the non-mandatory contracts signed by demand response aggregator and electric vehicle users,the distributionally robust optimization set based on the mean and variance is introduced;for the uncertainty caused by outdoor temperature,thedistributionally robust set based on the probability information of the environmental temperature subinterval is used to model.In the day-ahead market,the distributionally robust bidding decision-making nonlinear optimization model of demand response aggregator participating in the peak shaving service market is established,and the distributional opportunity constraint theory is introduced to reconstruct the model into a linear model.In the real-time scheduling,the real-time scheduling results of demand resources are obtained by adjusting the output plan in combination with the day-ahead bid winning situation.4.The feasibility and effectiveness of distributionally robust optimization methods are verified by simulation examples.Through scenarios design,the advantages and disadvantages of methods are compared with those of stochastic optimization and traditional robust optimization,and the influence of basic parameters such as maximum default probability and subinterval partition on the bidding decision results is analyzed.