The Impact of Customers' Demand Response Behaviors on Power System With Renewable Energy Sources

This article addresses a new approach to investigating the impact of demand response (DR) on the generation adequacy by considering customers' willingness to participate in DR. Firstly, to characterize psychological behaviors of the customer, we design a general reference-dependent utility (RU) function, and select the hyperbolic absolute risk aversion (HARA) function as the fundamental function to develop an HARA-RU (H-RU) function for depicting risk attitude of the customer. Secondly, a Q-learning algorithm based on the H-RU function is proposed to simulate customers' willingness to participate in DR. In this way, the available capacity of DR can be measured. Thirdly, based on the available capacity, a DR scheduling model is developed. And fourthly, according to the scheduling results, an assessment procedure is proposed to evaluate the impact of DR on generation adequacy. Finally, a case study is provided to verify the effectiveness of our method. Besides, one limitation of this study is that transmission congestions are not considered. In future research, it would be interesting to consider this factor and extend our method to the case of a more sophisticated situation.