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Cost optimization of a microgrid considering vehicle-to-grid technology and demand response

Title
Cost optimization of a microgrid considering vehicle-to-grid technology and demand response
Type
Article in International Scientific Journal
Year
2022
Authors
Beyazit, MA
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Tascikaraoglu, A
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Journal
Vol. 32
ISSN: 2352-4677
Publisher: Elsevier
Other information
Authenticus ID: P-00X-76S
Abstract (EN): Demand response (DR) programs can offer various benefits especially in microgrid environments with renewable energy systems (RESs) and energy storage technologies when effectively planned and managed. Accordingly, this study proposes an energy management approach for a neighborhood including residential end-users with photovoltaic (PV) systems, a shared energy storage system (ESS) and an electric vehicle (EV) fleet. The proposed approach presents a novel energy credit mechanism (ECM) for the EV fleet and households separately to exploit the EV batteries and store the excess PV energy in the neighborhood through the shared ESS for later use. End-users gain energy credits before a DR event and use these credits during the peak periods to minimize their total energy cost (TEC), resulted in a decrease in the peak demand. Also, the energy credits gained by the EV fleet are used through the vehicle-to-home (V2H) and vehicle-to-grid (V2G) services with the same objective. In order to conduct a more realistic analysis, a battery degradation cost estimation model is employed and the uncertain behavior of the EV users is considered. The case studies show that the proposed optimization strategy has the capability of considerably reducing the energy costs and peak demand.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 14
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