基于线性松弛最优潮流的电力市场日前出清及节点电价分解

Day-ahead power market clearing based on AC power flow can improve the security and give the result of reactive power allocation. To reduce the errors of current linearized AC optimal power flow, this paper decomposed the nonlinear part of the power flow equations into voltage amplitude part and phase part, which were relaxed into linear inequalities. A linear relaxation-based AC optimal power flow model (LR-ACOPF) was thus proposed. By LR-ACOPF model, a day-ahead power market clearing model considering reactive power constraints and transmission grid fees was built. Then, Karush-Kuhn-Tucker (KKT) condition was applied to derive price decomposition providing more specifically price messages. The paper transformed KKT conditions to linear equations having variables of price and constant terms of different dual variables. By solving linear equations corresponding to dual variables, the LMP, which is helpful for congestion management and voltage support analysis was provided. Case studies on IEEE systems and northwest China power grid demonstrated the effectiveness of the proposed method.