期刊
ELECTRIC POWER SYSTEMS RESEARCH
卷 106, 期 -, 页码 29-35出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2013.08.001
关键词
Smart Grid; Microgrid; Plug-in electric vehicle; Model predictive control
资金
- U.S. Department of Energy, Office of Science, Basic Energy Sciences [DE-AC02-06CH11357]
As an important component of Smart Grid, advanced plug-in electric vehicles (PEVs) are drawing much more attention because of their high energy efficiency, low carbon and noise pollution, and low operational cost. Unlike other controllable loads, PEVs can be connected with the distribution system anytime and anywhere according to the customers' preference. The uncertain parameters (e.g., charging time, initial battery state-of-charge, start/end time) associated with PEV charging make it difficult to predict the charging load. Therefore, the inherent uncertainty and variability of the PEV charging load have complicated the operations of distribution systems. To address these challenges, this paper proposes a model predictive control (MPC)-based power dispatch approach. The proposed objective functions minimize the operational cost while accommodating the PEV charging uncertainty. Case studies are performed on a modified IEEE 37-bus test feeder. The numerical simulation results demonstrate the effectiveness and accuracy of the proposed MPC-based power dispatch scheme. (C) 2013 Elsevier B.V. All rights reserved.
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