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PEV fleet scheduling with electricity market and grid signals Charging schedules with capacity pricing based on DSO's long run marginal cost

Electricity market signals are deemed efficient to allocate resources at the transmission system level, yet they may not always sufficiently represent the local network status of the distribution system. Furthermore, high penetration levels of Plug-in Electric Vehicles (PEV) potentially cause network reinforcement, which would have an impact on investment, operation and maintenance costs. While long run marginal cost pricing for computing node dependent network Use-of-System (UoS) tariffs has been proposed for integrating distributed generation, it remains unexplored in the context of PEV charging. Hence, this paper formulates the PEV energy retail problem with interactions in day-ahead and balancing markets from the aggregator's perspective, taking into account location dependent network UoS tariffs in the form of capacity prices for active power. While the retail tariff for the final customer is supposed fixed in the medium term, these capacity prices are accounted as costs to the aggregator. By aligning the PEV charging schedule, in time and location, to the network signals, the aggregator can hence further minimize its perceived costs. Applied to a medium voltage system with urban characteristics and spatial PEV mobility, profit optimal charging schedules for the aggregator are found. The result analysis and concluding remarks focus on the relevance of including node dependent network UoS tariffs.