Summary
Integration of highly volatile wind generation causes reliability and grid issues for system operator (SO). Plug‐in electric vehicles (PEVs) are mobile distributed source of active power that provides opportunity to use their battery storage for wind integration. The coordinated integration of wind volatility and PEVs fleet is studied under security‐constrained unit commitment (SCUC) model. In this regard, a stochastic SCUC with PEVs considering wind integration and line contingency is proposed. Wind volatility and PEVs driving behavior uncertainty is modeled through Monte Carlo simulations (MCS) of large number of scenarios with associated probabilities. This scenario has been reduced by Kantorovich distance (KD) matrix–based backward reduction technique. Moreover, pre‐line and post‐line contingency AC optimal power flow is used for network constraints in SCUC (AC SCUC). Due to consideration of N‐1 security criteria and wind power scenarios, the proposed model is mixed integer nonlinear programming (MINLP), which is computationally heavy and is thus solved by a two‐stage programming Benders decomposition (BD) approach. Different case studies are examined on modified IEEE reliability test system (RTS). Comparative analysis explores the impact on overall operational costs, PEV cost, wind curtailment, and locational marginal price (LMP) for congestion management. Simulation results validate that the proposed model is technoeconomically suitable for large‐scale wind power penetration.
Decarburization of electrical systems encourage high wind power into electric power systems and the electrification of transport sectors through electric vehicles (EVs). The increasing penetration of uncertain wind power generation and transportation networks via EV charging stations has introduced challenges for system operators to manage power systems and market operations. In this context, this paper presents a stochastic AC security-constrained unit commitment (SCUC) model to clear day-ahead energy and reserve markets considering transportationelectricity networks through EV charging stations in the presence of uncertain wind power and generator contingency. Pre-contingency ranking is a common strategy for reducing the time of the SCUC problem, but it provides high-impact outages. To address this issue, generator outages ranked first are identified using the postcontingency generator response ranking approach. The main contribution of this
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