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Managed Charging Dispatch Mechanisms: Trade-Offs and Opportunities

  • Idaho National Laboratory

Research output: NLR › Presentation

Abstract

Electric vehicle (EV) charging can be managed directly by an aggregator in coordination with supply-side dispatch, or it can be scheduled in response to prices. A previous production cost modeling study found that price-responsive mechanisms like time-of-use rates (TOU) and real-time prices (RTP), while providing more value than a low-error variant of aggregator-coordinated direct load control (DLC) at low levels of participation, were not able to provide production cost savings beyond 4% to 14% of light-duty vehicles participating. However, that study assumed day-ahead unit commitment decisions based solely on unmanaged charging profiles, i.e., with no foresight of price-responsive electric vehicle managed charging (EVMC). The study summarized in this presentation shows that two strategies - (1) improved forecasting of price-responsive EV charging and (2) flattening EV charging price-response over similarly priced times - can greatly increase the percentage of personal light-duty vehicles that can participate in TOU or RTP and still contribute to bulk power system cost reductions. Furthermore, the outcomes for price-responsive EVMC can be similar to or exceed those of DLC up to high participation levels, especially when charging is scheduled within single sessions using coarse price signals (time-of-use rates). Future modeling work will enable cost-optimal selection of DLC and TOU programs in power sector capacity expansion models. A separate project is exploring the concept of default-on Grid Aware charging that would create a more grid-friendly aggregate charging pattern by applying simple control strategies to a coarse database of basic, periodically updated grid information.
Original languageAmerican English
Number of pages21
DOIs
StatePublished - 2026

NLR Publication Number

  • NLR/PR-6A40-101686

Keywords

  • electric vehicle
  • managed charging
  • production cost modeling
  • vehicle grid integration

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