采用置信度风险测度的鲁棒发电计划模型及算法

针对大规模风电并网所带来的电网运行调度的不确定性及运行风险，提出基于置信度风险测度的鲁棒发电计划模型及求解算法。首先，提出一种新的风险测度—置信度风险测度（Risk_α），对于既定置信度α及相应的风电功率预测区间，以弃风风险值与切负荷风险值的和构成置信度综合风险测度，以量化风电实际功率超出风电可接纳域的风险。在此基础上，以发电成本和置信度风险之和最小为优化目标，构建计及置信度风险测度的鲁棒发电计划模型及分解求解算法，同时优化机组组合决策和风电可接纳域，使得所制定的发电计划方案实现经济性和运行风险之间的均衡。最后，通过算例证明算法的正确性及有效性。

Model and Algorithm of the Robust Generation Schedule Based on Confidence Risk Measurement

Aiming at the uncertainty and operational risk of grid operation scheduling brought about by large-scale wind power integration, a new confidence-risk-measurement-based model and its solution algorithm is proposed for robust generation schedule. The paper firstly proposes a new risk measurement, namely confidence risk measurement (Risk_α). For a given confidence level α and the corresponding wind power forecasting interval, the sum of the risk of wind curtailment and the risk of load shedding constitutes the confidence comprehensive risk measurement, which can be used for quantifying the risk caused by actual wind power surpassing the acceptable wind power threshold. And then, taking the sum of generation cost and confidence risk minimum as optimization objective, a new robust generation schedule model and its decomposition algorithm are proposed to simultaneously optimize the generator unit portfolio decision-making and the wind power acceptable threshold, thus making the formulated generation schedule achieve a balance between economy and operational risk. A case study has proved the correctness and effectiveness of the proposed model and algorithm.