University of Sussex
Browse
UoG-Arup_journal_v4f_not-marked.pdf (683.48 kB)

Decision tree aided planning and energy balancing of planned community microgrids

Download (683.48 kB)
journal contribution
posted on 2023-06-08, 23:00 authored by Panayiotis Moutis, Spyros Skarvelis-KazakosSpyros Skarvelis-Kazakos, Maria Brucoli
Planned Communities (PCs) present a unique opportunity for deployment of intelligent control of demand-side distributed energy resources (DER) and storage, which may be organized in Microgrids (MGs). MGs require balancing for maintaining safe and resilient operation. This paper discusses the implications of using MG concepts for planning and control of energy systems within PCs. A novel tool is presented, based on decision trees (DTs), with two potential applications: (i) planning of energy storage systems within such MGs and (ii) controlling energy resources for energy balancing within a PC MG. The energy storage planning and energy balancing methodology is validated through sensitivity case studies, demonstrating its effectiveness. A test implementation is presented, utilizing distributed controller hardware to execute the energy balancing algorithm in real-time.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Applied Energy

ISSN

0306-2619

Publisher

Elsevier

Volume

161

Page range

197-205

Department affiliated with

  • Engineering and Design Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2015-10-30

First Open Access (FOA) Date

2016-10-22

First Compliant Deposit (FCD) Date

2015-10-30

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC