Effective self-committed V2G for residential complexes
Sustainable Energy, Grids and Networks, ISSN: 2352-4677, Vol: 35, Page: 101114
2023
- 2Citations
- 20Captures
- 1Mentions
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Most Recent News
Findings on Sustainable Energy Grids and Networks Reported by Investigators at University of Ottawa (Effective Self-committed V2g for Residential Complexes)
2023 NOV 03 (NewsRx) -- By a News Reporter-Staff News Editor at Network Daily News -- Investigators discuss new findings in Energy Grids and Networks
Article Description
The challenges of the economic benefits of the vehicle-to-grid (V2G) concept grow when the energy market policymakers dominantly rely on the V2G revenue as an incentive for expanding the penetration of electric vehicles (EVs) in households and residential units. With restructuring the electricity markets to a self-committed model, some incentive and equity issues can be overcome, but that may suffer from inefficient scheduling and coordinating commitment between V2G units. This work discusses the operational constraints in utilizing V2Gs in residential complexes and addresses them by constructing a composite optimization problem with a heuristic boundary selection. We considered the battery cost, the number of V2G units in a residential complex, the number of V2G event cycles during the EV lifetime, and energy arbitrage net revenue to study the financial and operational effectiveness of V2G programs. We examined the proposed solution through two case studies and demonstrated the optimal self-commitment and scheduling of the V2G program by reinforcing the feasible and economical boundaries. Finally, simulation outcomes show designating the boundaries using heuristic search and employing proposed composite optimization results in a lower operating cost compared to other conventional unit commitment techniques.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2352467723001224; http://dx.doi.org/10.1016/j.segan.2023.101114; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85166938290&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2352467723001224; https://dx.doi.org/10.1016/j.segan.2023.101114
Elsevier BV
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