User response policy optimization method for stimulative power demand response

Abstract

The invention discloses a user response policy optimization method for stimulative power demand response. The method comprises the steps of confirming a resource parameter of a user; building a user cost benefit model and setting an objective function; building a user reliability quantitative model and setting an objective function; combining the two objective functions into a multi-objective optimization model; solving the model by adopting a multi-objective genetic algorithm NSGA-II to obtain a Pareto non-inferior solution set of a user response policy and an optimization result set consisting of user profits and user comprehensive reliability indexes; calculating normalized Euclidean distances between all optimization results and constructed ideal results; and according to the normalized Euclidean distances, sorting the optimization results to form a to-be-evaluated set, evaluating the optimization results in the to-be-evaluated set by adopting an entropy weighting double points method, and finally obtaining an optimal user response policy. According to the method, the economy and reliability of the user are balanced; a reasonable response sequence can be given for multiple users participating in response together; and the method is especially suitable for optimization of the response policies of the multiple users.

Description

technical field [0001] The invention relates to the optimization problem of electric power demand response, in particular to a user response strategy optimization method of incentive electric power demand response, which belongs to the field of electrical engineering. technical background [0002] With the emergence of the energy crisis in recent years, relying on the rapid development of smart grids, demand response projects have attracted more and more people's attention, and they have been piloted in some cities in my country. As an important measure of demand side management, incentive demand response plays an important role in optimizing supply and demand balance and power resource allocation. In addition, the emergence of load aggregators provides opportunities for small and medium-sized multiple users with different electricity consumption characteristics to participate in market regulation, and fully taps the scheduling potential of user-side resources. Since the re...

AI Technical Summary

Problems solved by technology

Traditional power user reliability indicators cannot reflect the impact of participating in demand response on user reliability. If the reliability impact is not quantified, users will not be able to intuitively understand the impact of participation in response projects on their own reliability.

If the research on the optimal response strategy on the user side fails to consider user reliability, it may lead to an imbalance between the user's economy and reliability

In addition, the joint participation of multiple users makes it difficult for load aggregators to reasonably arrange user response sequences

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