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Modeling the Benefits of Vehicle-to-Grid Technology to a Power System

handle: 20.500.11937/19128
Electric vehicle (EV) numbers are expected to significantly increase in the coming years reflecting their potential to reduce air pollutants and greenhouse gas emissions. Charging such vehicles will impose additional demands on the electricity network but given the pattern of vehicle usage, the possibility exists to discharge the stored energy back to the grid when required, for example when lower than expected wind generation is available. Such vehicle-to-grid operation could see vehicle owners supplying the grid if they are rewarded for providing such services. This paper describes a model of an electric vehicle storage system integrated with a standardized power system (the IEEE 30-node power system model). A decision-making strategy is established for the deployment of the battery energy stored, taking account of the state of charge, time of day, electricity prices and vehicle charging requirements. Applying empirical data, the benefits to the network in terms of load balancing and the energy and cost savings available to the vehicle owner are analyzed. The results show that for the case under study, the EVs have only a minor impact on the network in terms of distribution system losses and voltage regulation but more importantly the vehicle owner's costs are roughly halved.
- University of Strathclyde United Kingdom
- Curtin University Australia
629, Electrical engineering. Electronics Nuclear engineering
629, Electrical engineering. Electronics Nuclear engineering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).228 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
