Multi-objective Dynamic Optimal Power Flow of Wind Integrated Power Systems Considering Demand Response

This paper studies the economic environmental energy-saving day-ahead scheduling problem of power systems considering wind generation (WG) and demand response (DR) by means of multi-objective dynamic optimal power flow (MDOPF). Within the model, fuel cost, carbon emission and active power losses are taken as objectives, and an integrated dispatch mode of conventional coal-fired generation, WG and DR is utilized. The corresponding solution process to the MDOPF is based on a hybrid of a non-dominated sorting genetic algorithm-II (NSGA-II) and fuzzy satisfaction-maximizing method, where NSGA-II obtains the Pareto frontier and the fuzzy satisfaction-maximizing method is the chosen strategy. Illustrative cases of different scenarios are performed based on an IEEE 6-units \ 30-nodes system, to verify the proposed model and the solution process, as well as the benefits obtained by the DR into power system.