2017
DOI: 10.1016/j.egypro.2017.03.586
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A Collaborative Decision Model for Electric Vehicle to Building Integration

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Cited by 23 publications
(4 citation statements)
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References 12 publications
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“…In the example in [48], a method based on linear programming is developed, where the objective of this one is to minimize the operational cost of the building in question, where it benefits from PV production and the EV charging station that collaborated. With this method, it is concluded that the collaborative strategy between the building and the EV charging station is more economical than the non-collaborative strategy.…”
Section: Vehicle-to-buildingmentioning
confidence: 99%
“…In the example in [48], a method based on linear programming is developed, where the objective of this one is to minimize the operational cost of the building in question, where it benefits from PV production and the EV charging station that collaborated. With this method, it is concluded that the collaborative strategy between the building and the EV charging station is more economical than the non-collaborative strategy.…”
Section: Vehicle-to-buildingmentioning
confidence: 99%
“…In the example in [132], an average office building is considered with photovoltaic energy contribution, electrical and thermal storage, and a series of electrical and thermal loads. The resolution method seeks the Pareto Frontier between the cost of vehicles charging and building energy cost.…”
Section: Vehicle-to-building (V2b)mentioning
confidence: 99%
“…The significant performance improvement is because our system exploits the EV battery capacity more fully and thus permits large rooftop solar installations without wasting generated power on sunny days. In summary, none of the works reviewed in Section 2 on combining V2B and local renewable generation has a problem formulation that permits effective exploitation of the potential EV battery storage capacity for a large fleet of EVs, with the exception of [33]. However, the 24% saving reported in [33] was obtained by ignoring battery degradation cost, simulating only one sunny day in the summer and by neglecting uncertainties related to building electricity consumption and EV behaviour.…”
Section: Comparison With the State Of The Artmentioning
confidence: 99%
“…Reference [33] claims 24% cost savings based on simulating one sunny day in the summer in Chicago, but battery degradation costs are not considered and uncertainties in building energy consumption and EV behavior are left for further work. Reference [34] focusses on households and small buildings and does not provide comparable savings data; uncertainty in EV behavior is also neglected.…”
Section: Related Research In Electric Vehicle Battery Exploitationmentioning
confidence: 99%