4.7 Article

Tri-Level Scheduling Model Considering Residential Demand Flexibility of Aggregated HVACs and EVs Under Distribution LMP

期刊

IEEE TRANSACTIONS ON SMART GRID
卷 12, 期 5, 页码 3990-4002

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2021.3075386

关键词

HVAC; Load modeling; State of charge; Smart grids; Schedules; Reactive power; Static VAr compensators; EV aggregator; HVAC aggregator; distribution locational marginal price (DLMP); residential demand flexibility; tri-level scheduling model; load shift; DLMP step change

资金

  1. U.S. Department of Energy (DOE), including DOE's Grid Modernization Laboratory Consortium (GMLC), Office of Electricity, and Building Technologies Office
  2. U.S. National Science Foundation (NSF)
  3. DOE under NSF [EEC-1041877, TSG-01569-2020]

向作者/读者索取更多资源

This paper introduces EV and HVAC aggregator models and establishes a three-level bidding and dispatching framework. Case studies reveal three main technical reasons for payment reduction due to demand flexibility.
Residential loads, especially heating, ventilation and air conditioners (HVACs) and electric vehicles (EVs), have great potentials to provide demand flexibility which is an attribute of grid-interactive efficient buildings (GEB). Under this new paradigm, EV and HVAC aggregator models are first developed in this paper to represent the fleet of GEBs, in which the aggregated parameters are obtained based on a new approach of data generation and least squares parameter estimation (DG-LSPE), which can deal with heterogeneous HVACs. Then, a tri-level bidding and dispatching framework is established based on competitive distribution operation with distribution locational marginal price (DLMP). The first two levels form a bilevel model to optimize the aggregators' payment and to represent the interdependency between load aggregators and the distribution system operator (DSO) using DLMP, and the third level is to dispatch the optimal load aggregation to all residents by the proposed priority list-based demand dispatching algorithm. Finally, case studies on a modified IEEE 33-Bus system illustrate three main technical reasons of payment reduction due to demand flexibility: load shifts, DLMP step changes, and power losses. They can be used as general guidelines for better decision-making for future planning and operation of demand response programs.

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