Optimal day-ahead scheduling of multiple integrated energy systems considering integrated demand response, cooperative game and virtual energy storage

As the physical carrier of the Energy Internet, integrated energy system (IES) is a future development trend in the energy field, and the optimal scheduling of IES for improving energy utilisation efficiency has become a hot topic. An optimal day-ahead scheduling model of multiple IESs considering integrated demand response (IDR), cooperative game and virtual energy storage (VES) is proposed innovatively in this study to maximise the overall benefits of the cooperative alliance. IDR and VES are considered together for the first time to optimise the internal scheduling of each IES, where IDR can enhance the response potential on the demand side and VES can improve the scheduling flexibility of IES. Cooperative game theory is utilised to process the energy trading mechanism among multiple IESs and the Nash bargaining method is utilised to solve the cooperative game problem and obtain a fair and Pareto-optimal energy trading strategy. The case study shows that the proposed model effectively improves the operating benefits and the renewable energy penetration levels of each IES.

Automated summary

Integrated energy system (IES) is a future trend in the energy field, with an optimal day-ahead scheduling model proposed in this study considering integrated demand response, cooperative game, and virtual energy storage to maximize overall benefits. The model effectively improves operating benefits and renewable energy penetration levels of each IES, showcasing the importance of cooperative strategies in energy trading.