Domestic Battery Power Management Strategies to Maximize the Profitability and Support the Network

Ahmed A.Raouf Mohamed, Robert Best, Xueqin Amy Liu, D John Morrow

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)
251 Downloads (Pure)

Abstract

Behind the meter battery energy storage systems (BESS) are attracting more customers due to their ability to achieve a profitable energy arbitrage in the presence of electric vehicles (EV) and solar photovoltaics (PV) with the time of use tariffs. From the distribution system operator’s perspective, these units can be utilized to support the network, especially with the rapid deployment of microgeneration and the electrification of transportation and heat. This paper proposes two management algorithms to maximize the customer’s profitability and support the network’s operation. The first algorithm is day-ahead scheduling that utilizes the forecasted data to solve a bi-objective function that optimizes the electricity bill and the load variance. The second algorithm is a rule-based strategy executed in a real-time based on a set of inputs and rules to maximize the battery’s returned value and mitigate the impact of a household’s net demand on the network. Both algorithms were validated using actual measurements and compared against the conventional rule-based management strategy, while the impact on the network was analyzed using real network data located in Northern Ireland.
Original languageEnglish
Title of host publication IEEE PES General Meeting 2021: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
DOIs
Publication statusPublished - 20 Dec 2021
EventIEEE PES General Meeting 2021 -
Duration: 25 Jul 202129 Jul 2021

Publication series

NameIEEE Power Engineering Society General Meeting
ISSN (Electronic)1932-5517

Conference

ConferenceIEEE PES General Meeting 2021
Period25/07/202129/07/2021

Keywords

  • Battery energy storage systems
  • electric vehicles
  • power management
  • scheduling
  • solar photovoltaic

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  • Residential Battery Management Tool (RBMT)

    Mohamed, A. A. R. (Developer), Oct 2020

    Research output: Non-textual formSoftware

    Open Access

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