Hierarchical energy management mechanisms for an electricity market with microgrids
- Author(s): Hong-Tzer Yang 1 and Jian-Tang Liao 1
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View affiliations
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Affiliations:
1:
Department of Electrical Engineering , Research Center for Energy Technology and Strategy , National Cheng Kung University , Tainan , Taiwan
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Affiliations:
1:
Department of Electrical Engineering , Research Center for Energy Technology and Strategy , National Cheng Kung University , Tainan , Taiwan
- Source:
Volume 2014, Issue 8,
August
2014,
p.
477 – 486
DOI: 10.1049/joe.2014.0185 , Online ISSN 2051-3305
This study addresses a micro-grid electricity market (MGEM) with day-ahead (DA) and real-time market mechanisms integrated. The bidding mechanisms for the market are described in this study, considering the generation cost of different distributed energy resources (DERs), like distributed generator, energy storage system and demand response. Including load and renewable generation forecasting systems and a fuzzy decision supporting system, a hierarchical micro-grid energy management system (MG-EMS) is then proposed to ensure the benefits of involved micro-grid central controller, DER owners and customers. To verify the feasibility of the proposed system, the whole-year historical pricing and load data for New England independent system operator are employed. The numerical results show that the proposed MG-EMS is promising and effective for the operations of MGEM.
Inspec keywords: power markets; power distribution economics; power generation economics; power engineering computing; pricing; distributed power generation; demand forecasting; decision support systems; fuzzy set theory; load management; power distribution control; control engineering computing; power generation control; demand side management
Other keywords: bidding mechanisms; DER; real-time market mechanism; fuzzy decision supporting system; load data; hierarchical energy management mechanisms; microgrid central controller; day-ahead market mechanism; New England independent system operator; energy storage system; generation cost; load generation forecasting systems; distributed generator; whole-year historical pricing; microgrid electricity market; MGEM; distributed energy resources; demand response; renewable generation forecasting systems
Subjects: Distribution networks; Power system management, operation and economics; Control engineering computing; Combinatorial mathematics; Decision support systems; Combinatorial mathematics; Distributed power generation; Control of electric power systems; Power system control; Power engineering computing
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