Conditional value-at-risk-based optimal spinning reserve for wind integrated power system

In wind-integrated power systems, the stochastic and random wind power brings more uncertainties to power system operation. To address multiple uncertain factors including wind power forecast error, generator failure, and load forecast error, a conditional value-at-risk (CVaR)-based optimal spinning reserve determination method for wind-integrated power system is proposed in this paper with consideration of both reliability and economy of system operation under a certain level of risk. The CVaR model of spinning reserve considering different uncertain factors is built and then incorporated into the coordinated scheduling model of power generation and spinning reserve in wind integrated power system. The optimization model is solved by mix integer linear programming, and the CVaR-based spinning reserve allocation and the power output of each unit are optimally determined at a certain confidence level. The proposed method can provide a trade-off between the economy and reliability of system operation with respect to the confidence level of risk. Simulation results on 10-unit system and 100-unit system demonstrate the effectiveness of the proposed method. Copyright (C) 2016 John Wiley & Sons, Ltd.