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

Long Wu, Xunyuan Yin, Lei Pan and Jinfeng Liu

Applied Energy, 2022, vol. 328, issue C, No S0306261922014441

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

Keywords: Integrated energy systems; Time-scale multiplicity; Subsystem decomposition; Economic model predictive control; Zone tracking (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2022.120187

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