IEEE Transactions on Smart Grid · 2019 · 29 citations · 30 references
ManagementBusiness EconomicsEconomicsCapacity PlanningEnergy EconomicsForecastingCapacity ForecastingCost ForecastingDistributed Energy ResourcesElectricity MarketsEnergy Demand ForecastingLoad ForecastingDay-ahead Electricity MarketsDistributed Energy Resources IntegrationDistributed Energy SystemsEstimated CostsOpportunity Cost ValuationPrediction IntervalsReal-time Electricity MarketsWholesale Energy Markets
A large number of mechanisms are proposed to manage potential problems in distribution networks caused by the participation of distributed energy resources (DERs) in the wholesale markets. In this paper, we first introduce a practical and straightforward mechanism, based on capacity limits, which avoids conflicts between the transmission system operator and the distribution system operators (DSOs). Using a large number of real electric vehicle (EV) commercial charging stations we then show how an EV aggregator can forecast the opportunity cost incurred by offering a mid-term capacity limit service to the DSO. This cost is computed based on the estimated profit that the aggregator could gain in the day-ahead and real-time markets. The proposed methodology guarantees robustness against evolving EV uncertainty, both in terms of service delivery and driving requirements. It also allows the use of a variety of time-series forecasting methods without forecasting electricity prices and EV scenarios. The results of our empirical analysis show the exponential increase of opportunity cost and the considerable increase of the prediction intervals as the capacity limit decreases. The produced offering curves can be used as an indication of the underutilization cost of DERs caused by the DSO's limitations.
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