Economic Model Predictive Control for Energy Systems in Smart Homes

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Abstract

In this paper we present simulations of Economic Model Predictive Control (EMPC) for control of the energy system in a smart home. The energy system in a smart home consists of a stationary battery, photo voltaic solar cells on the roof, a heat pump for heating, and an electrical vehicle battery that is charged. Using weather forecasts, thermal comfort and driving profiles, the EMPC coordinates this energy system and its interaction with the external energy system by purchasing and selling electricity at prices that are announced in advance. The EMPC is a linear program with soft constraints for the output constraints and an objective function that represents the cost of energy. In contrast to existing methods, the key novelties in the present paper is the use of multi-level soft constraints and an objective function that accounts not only for the cost of energy used during the prediction horizon but also for the value of energy stored at the end of the prediction horizon. We demonstrate by simulation, that these novelties are important for well-behaved closed-loop performance of the EMPC.
Original languageEnglish
Title of host publicationProceedings of 2019 IEEE Conference on Control Technology and Applications
PublisherIEEE
Publication date2019
Pages598-604
ISBN (Print)9781728127668
DOIs
Publication statusPublished - 2019
Event2019 IEEE Conference on Control Technology and Applications (CCTA) - City University of Hong Kong, Hong Kong, China
Duration: 19 Aug 201921 Aug 2019
Conference number: 3
https://ccta2019.ieeecss.org/

Conference

Conference2019 IEEE Conference on Control Technology and Applications (CCTA)
Number3
LocationCity University of Hong Kong
CountryChina
CityHong Kong
Period19/08/201921/08/2019
Internet address

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