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Intelligent demand response for industrial energy management considering thermostatically controlled loads and EVs

Wang, Jidong, Shi, Yingchen and Zhou, Yue 2019. Intelligent demand response for industrial energy management considering thermostatically controlled loads and EVs. IEEE Transactions on Industrial Informatics 15 (6) , pp. 3432-3442. 10.1109/TII.2018.2875866

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Abstract

In this paper, an intelligent energy management framework with demand response capability was proposed for industrial facilities. The framework consists of multiple components, including industrial processes modeled by the state task network (STN) method, thermostatically controlled loads (TCLs) like the heating, ventilation and air conditioning (HVAC) system with chilled water storage (CWS), renewable generation like photovoltaic (PV) arrays and electric vehicles (EVs). These components were firstly modeled and the operation of them is then optimized in time-of-use (TOU) pricing schemes. Factors that affect several components at the same time, e.g. the number of workers, are considered. The optimization is formulated as a mixed integer linear programming (MILP) problem. A general tire manufacturing facility was investigated as the case study. Simulation results show that the proposed intelligent industrial energy management (IIEM) with DR is able to effectively utilize the flexibility contained in all parts of the facility and reduce the electricity costs as well as the peak demand of the facility, while satisfying all the operating constraints.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 1551-3203
Date of First Compliant Deposit: 18 October 2018
Date of Acceptance: 26 September 2018
Last Modified: 05 Aug 2019 14:59
URI: http://orca.cf.ac.uk/id/eprint/115988

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