Study On Day-ahead Optimal Scheduling Model With Demand Response

With the development of competitive electricity market, the stakeholders tend to be diversified and demand side is no longer the traditional electric consumers. In order to effectively promote the optimization of power system operation, demand response is incorporated into the day-ahead optimal scheduling to realize the coordinated scheduling of both generation side and demand side resources. Based on such backgrounds, the main contents and original contributions of this paper are as follows:Firstly, the concept of demand response is introduced. DR could generally be divided into price-based DR and incentive-based DR. The price-based DR is modeled based on price elasticity and customer benefit function to quantify participant’s response to price, which lay the foundation for the subsequent work.Then the day-ahead scheduling of price-based DR is studied. Under the background of price-based DR participating in grid interaction, this paper explores the establishment of day-ahead generation scheduling model integrated with more flexible price-based DR based on the day-ahead time-of-use tariff operation experiences in Europe. Multi-objective optimization and multi attribute decision making techniques are used to solve the comprehensive optimization of various objectives in the proposed model. Firstly, price-based DR is incorporated into the day-ahead unit commitment to establish a day-ahead multi-objective scheduling model, which takes into account both the system economical operation and the economical benefit of DR participants. Secondly, a price-based DR multi attribute decision making based day-ahead scheduling model is proposed which selects the optimal price, calculates the equivalent generation load curve of the next day and finally solves the day-ahead generation scheduling problem.Finally, the coordinated optimization of incentive-based demand response is studied. Two DR programs, namely, load reduction demand response (LRDR) and load transfer demand response (LTDR) are proposed and their models are extended with a refined description by adding various constraints. Then the day-ahead joint scheduling mode with DR is studied. Finally, a co-optimized day-ahead energy/res-erve scheduling model integrated with DR is established.The effectiveness of the proposed models is verified on a modified IEEE 118-bus system.