The endeavor for a more sustainable power generation has led to a dramatic increase in power generation from renewable energy sources (RES), such as wind and solar. These sources are of fluctuating nature and therefore introduce new challenges to power system operation, which was historically designed for generators with constant infeed. The fluctuations are balanced by ancillary services contracted from flexible generators or storages. So far, large scale solutions for storage are only provided by pumped hydro. However, one potential solution for a large storage could be to aggregate Plug-In Hybrid Electric Vehicles (PHEVs), once they are adopted on a wide scale, into a virtual storage. This storage could then be used to balance the infeed error of RES. The balancing would imply that the PHEVs could be recharged from emission free sources, thereby enabling an emission free individual transportation sector. This paper focuses on the realization of an aggregated PHEV storage and the balancing of RES infeed errors. In specific, the paper investigates how a large fleet of PHEVs can be aggregated over a large, urban electricity distribution network and how this storage can be used to balance a wind infeed error while considering the limits of the underlying infrastructure. The balancing can be achieved through so called vehicle-to-grid (V2G) services which allow PHEVs to act both as loads and as generators. The utilized aggregation scheme is based on an intelligent PHEV charging control scheme which avoids negative network impacts, such as overloading of assets, from excessive PHEV charging. V2G services are added on top of this intelligent recharging infrastructure. The paper shows that by using a Model Predictive Control (MPC) approach as a controller for the aggregated PHEV storage, an intrahour wind infeed error from a 500 MW wind park can be fully balanced while keeping the underlying distribution network in a secure state.
Balancing renewable energy source with vehicle to grid services from a large fleet of plug-in hybrid electric vehicles controlled in a metropolitan area distribution network. Zowards the power system of the future modelling/new tools for technical performance assessment
2011
18 Seiten, 13 Bilder, 19 Quellen
Aufsatz (Konferenz)
Datenträger
Englisch
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