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MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Wang, Jidong, Li, Chenghao, Li, Peng, Che, Yanbo, Zhou, Yue and Li, Yinqi 2019. MPC-based interval number optimization for electric water heater scheduling in uncertain environments. Frontiers in Energy 10.1007/s11708-019-0644-9
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Abstract

In this paper, interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling. First of all, interval numbers are used to describe uncertain parameters including hot water demand, ambient temperature, and real-time price of electricity. Moreover, the traditional thermal dynamic model of electric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling problem with uncertain parameters is formulated, and solved by interval number optimization. Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices. Furthermore, the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day. Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand, ambient temperature, and real-time price of electricity, enabling customers to flexibly adjust electric water heater control strategy.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Engineering
Publisher: Springer Verlag (Germany)
ISSN: 2095-1701
Date of First Compliant Deposit: 2 October 2019
Date of Acceptance: 7 May 2019
Last Modified: 19 Oct 2019 05:41
URI: http://orca.cf.ac.uk/id/eprint/125496

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