Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm

Abstract—It is extremely difficult to realize real-time active-reactive optimal power flow (RT-AR-OPF) in distribution networks (DNs) with wind stations (WSs) due to the conflict between the fast changes in wind power and the slow response from the optimization computation. To address this problem,...

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Vydáno v:Renewable energy Ročník 126; s. 509 - 523
Hlavní autoři: Mohagheghi, Erfan, Gabash, Aouss, Alramlawi, Mansour, Li, Pu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.10.2018
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ISSN:0960-1481, 1879-0682
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Shrnutí:Abstract—It is extremely difficult to realize real-time active-reactive optimal power flow (RT-AR-OPF) in distribution networks (DNs) with wind stations (WSs) due to the conflict between the fast changes in wind power and the slow response from the optimization computation. To address this problem, a new lookup-table-based RT-AR-OPF framework is developed in this paper. According to the forecasted wind power for a prediction horizon, scenarios are generated based on its stochastic distribution. The corresponding mixed-integer nonlinear programming (MINLP) problems are solved online which simultaneously optimize the active and reactive power dispatch of WSs, active-reactive reverse power flow, and discrete slack bus voltage, resulting in a lookup table. Based on the actual wind power available in a sampling time, one of the solutions will be selected and realized to the DN. A new reconciliation algorithm is proposed to ensure both the feasibility and optimality of the realized operation strategy. The applicability of the proposed framework is shown using a medium-voltage DN. •A novel RT-AR-OPF framework for very short sampling time is developed.•MINLP OPF problems with bidirectional active-reactive power flow are online solved.•A reconciliation algorithm is proposed to overcome potential convergence problems.•A power factor modification algorithm is introduced to ensure feasible operations.•The proposed method ensures the feasibility and optimality of operation strategies.
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ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2018.03.072