期刊
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
卷 56, 期 5, 页码 5543-5552出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2020.3000707
关键词
Resistance heating; Cooling; Load modeling; Uncertainty; Cogeneration; Optimization; Energy storage; Electrical energy storage; energy hub (EH); optimal operation; stochastic programming
资金
- FEDER funds through COMPETE 2020
- Portuguese funds through FCT [POCI-01-0145-FEDER-029803 (02/SAICT/2017)]
- VILLUM FONDEN under the VILLUM Investigator Grant [25920]
This article presents a robust chance-constrained optimization framework for the optimal operation management of an energy hub (EH) in the presence of electrical, heating, and cooling demands, and renewable power generation. The proposed strategy can be used for optimal decision making of operators of EHs or energy providers. The electrical energy storage device in the studied EH can handle the fluctuations in operating points raised by such uncertainties. In order to model the hourly demands and renewable power generation uncertainties, a robust chance-constrained close-to-real-time model is adopted in this article. The considered EH in this study follows a centralized framework and the EH operator is responsible for the optimal operation of the hub assets based on the day-ahead scheduling. A thorough analysis of energy flows with different carriers is presented. In addition, a numerical stability test regarding the selection of the time step size is performed to guarantee the solution's time resolution independence, occurring in previous studies.
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