A two-stage demand response strategy for multiple scenarios based on deviation compensation

Abstract

Integrated demand response (IDR) is an integral part of the park-level integrated energy system (PIES). Most existing IDR strategies depend heavily on explicit forecasts of future uncertainties. Due to the randomness of wind power generation and load demands, these approaches are limited by forecasting response time or accuracy. A two-stage demand response strategy for multiple scenarios based on deviation compensation is proposed to consider prediction uncertainties arising in distributed wind power generation and multi-energy load. In the day-ahead stage, considering the impact of energy prices on the economy of PIES operation, it is proposed to divide PIES operation scenarios based on energy prices. It is also proposed to develop a day-ahead response plan considering the demand response capability of the load side. The real-time stage considers the uncertainty of wind power and load forecasting as well as the real-time response speed of the strategy, and proposes to use deviation compensation to change some day-ahead plans in order to solve the uncertainty of prediction. Finally, considering the synergy between energy storage and demand response strategies, the above demand response strategy is embedded into multi-objective Harris Hawk optimization (MOHHO) to work out the energy storage capacity. The simulation results show that the strategy considers multiple operational scenarios, is more economical, and only changes a portion of the day-ahead plan in the real-time phase, so it has faster real-time response speed.