A multi-time-space scale optimal operation strategy for a distributed integrated energy system

Integrated energy system (IES) has become a popular topic in the field of energy research, and a considerable part of this research has paid attention to IES operation. However, regarding a distributed integrated energy system (DIES) with multiple communities, the coordination of multiple operation measures on different time and space scales has not been fully considered. Based on these considerations, a multi-time-space scale optimal operation strategy based on multi-dimensional energy supply and demand balance is proposed for a DIES. First, from the perspective of energy supply and demand, various types of energy equipment are modelled and analysed to propose a multi-dimensional energy supply and demand balance model. Moreover, a collaborative optimization framework and a multi-time-space scale operation model of DIES that comprises upper, middle and lower levels are further established. While the upper-level model optimizes the whole DIES in the day-ahead stage, the middle-level model performs a rolling optimization for each single community during the intraday, and the lower-level model achieves an adjustment of the electric part of each community in the real-time stage. Finally, a case study is carried out based on a practical town area, and simulation results show that the proposed strategy can utilize the complementary advantages of multiple energy sources and promote the energy supply and demand balance at multiple time and space scales, while exhibiting better performances in terms of objectives, constraints, operation measures and economics.

Automated summary

The study proposes a multi-time-space optimal operation strategy for distributed integrated energy systems, which includes a collaborative optimization framework and operation models on different time scales. The strategy aims to achieve coordination of multiple operation measures in a community-based integrated energy system, promoting energy supply and demand balance.