Economic model predictive control of integrated energy systems: A multi-time-scale framework

An integrated energy system (IES) that comprises diverse operating units typically exhibits time-scale multiplicity in its dynamics, which makes the application of predictive control schemes to such an IES challenging. In this work, a multi-time-scale framework for subsystem decomposition and corresponding economic model (EMPC) design is proposed explicitly address time-scale-multiplicity optimal IESs. Specifically, stand-alone considered. According multiplicity, decomposed into three reduced-order subsystems with slow, medium, fast dynamics. A composite EMPC (CEMPC) designed based on dynamically coordinate operations units, aiming at meeting customers’ electricity cooling demands while reducing fuel consumption. CEMPC, zone tracking objective building temperature regulation adopted maintain thermal comfort, reduce costs, achieve more degrees freedom satisfying demands. The CEMPC composed short-term distributed long-term EMPC. consists local EMPCs medium dynamics IES. optimizes taking account forecasts external conditions. These communicate cooperate decision-making. Extensive simulations are carried out evaluate performance compared hierarchical real-time optimization (HRTO) framework. simulation results show can increase system’s overall by about 5% if set-point used 30% incorporated. also much computationally efficient reduces computation time over 65%. fully leverages capability each unit provide superior load maintaining comfort. Our studies indicate approach significantly enhances operational flexibility IESs customized requirements.