Optimal operation of urban multi-energy system via coordination of waste resourceful utilization and multi-energy storage

• A novel urban multi-energy system framework with UWRUS and MESS has been proposed based on the analysis of energy storage and release characteristics. • Considering the relationship between urban waste disposal process and the energy supply and demand characteristics, the cooperative operation strategy of UWRUS, MESS and urban multi-energy system has been proposed. • Considering the relationship and coordination ability between waste resourceful utilization and energy supply, the urban multi-energy system optimal operation model based on UWRUS and MESS collaborative has been established. As promising means to improve urban waste disposal utilization and the comprehensive energy supply efficiency, the coordinated operation mode of waste energy supply and urban multi-energy system needs to make a profound study. However, the existing operation optimization theory ignores the interaction between waste energy supply, energy storage system and urban energy system , which will make it difficult to maximize waste energy supply and renewable energy utilization. In this study, an urban multi-energy system framework with waste resourceful utilization system (UWRUS) and multi-energy storage system (MESS) is proposed. Firstly, an UWRUS model is established by the relationship between the waste output, the maximum waste stockpile and the corresponding energy supply characteristics. Then, a MESS model is proposed to improve the multi-energy system operation flexibility. On this basis, an urban multi energy system optimal model based on waste resourceful and multi-energy storage collaborative is established. Finally, the proposed method is tested and verified by simulation comparison analysis. The results and experiences of the case studies show that the proposed coordinated model can improve the energy efficiency and operation economy. The energy utilization efficiency is 7.8 % more and total operation cost is 18.4 % less compared with existing methods.