Two-stage Dual-loop Optimal Control Strategy Based on Model Predictive Control for Integrated Energy Systems

Abstract

Integrated energy systems (IES) can effectively improve energy efficiency and have received extensive attention in recent years. However, the source-load fluctuations and multi-time scale characteristics of energy flows pose challenges for optimal operation control of the system, especially affecting the stable operation of the main grid. In this paper, we propose a two-stage dual-loop optimal control strategy for IES, which includes: (1) day-ahead economic optimal scheduling (DEOS), and (2) intraday dual-loop rolling optimization control strategy (ROCS) based on model predictive control. In DEOS, the day-ahead optimal economic dispatch is obtained by minimizing the system operating cost. In ROCS, considering the different time scales of cooling, heating, and power responses, the equipment output power is adjusted based on the short-term source-load forecast to suppress main grid and energy storage fluctuations. To demonstrate the performance of the proposed strategy, a typical IES is analyzed and simulation results are given in case studies.