姚俊伟,何奇,张宇,谢琼瑶,王海亮,邓玲,胡长宇
YAO Junwei,HE Qi,ZHANG Yu,XIE Qiongyao,WANG Hailiang,DENG Ling,HU Changyu

• 1:国网湖北省电力有限公司宜昌供电公司
• 2:宜昌电力勘测设计院有限公司(国网宜昌供电公司经济技术研究所)
• 3:梯级水电站运行与控制湖北省重点实验室(三峡大学)

摘要(Abstract)：

为有效应对风电机组出力的不确定因素对微电网安全经济运行的影响，提出了考虑风电出力不确定性的微电网两阶段分布鲁棒优化调度模型。首先，利用改进DNN（深度神经网络）对风电场进行出力预测，计算预测误差；然后，采用非参数核密度估计方法对预测误差数据进行分析，依据误差累积概率密度曲线构建盒式不确定集；接着，建立min-max-min结构的微电网两阶段鲁棒优化调度模型；最后，运用强对偶理论将原问题分解为混合整数线性规划的主问题和子问题，通过迭代求解得到最优调度方案。算例结果表明，所提模型相较于传统两阶段鲁棒优化模型具备更强的鲁棒性。
To effectively address the impact of uncertainties in wind turbine output on the safe and economical operation of microgrids, this paper proposes a two-stage distributed robust optimal scheduling model for microgrids that accounts for these uncertainties. First, an improved deep neural network(DNN) is used to forecast the output of wind farms, and the forecasting error is calculated; then, a non-parametric kernel density estimation method is employed to analyze the forecasting error data, and a box type uncertainty set is constructed using the cumulative probability density curve of the error. Next, a two-stage robust optimal scheduling model with a min-max-min structure for microgrids is established. Finally, strong duality theory is applied to decompose the original problem into a master problem and subproblem, both of which are formulated as mixed-integer linear programming problems, and the optimal scheduling scheme is obtained through iterative solving. The case study results show that the proposed model demonstrates stronger robustness compared to traditional two-stage robust optimal models.

关键词(KeyWords)： 两阶段鲁棒优化;非参数核密度估计;盒式不确定集;微电网经济调度
two-stage robust optimal;non-parametric kernel density estimation;box type uncertainty set;economical microgrid dispatching

Abstract:

Keywords:

基金项目(Foundation): 湖北省自然科学基金联合基金（2022CFD167）

作者(Author): 姚俊伟,何奇,张宇,谢琼瑶,王海亮,邓玲,胡长宇
YAO Junwei,HE Qi,ZHANG Yu,XIE Qiongyao,WANG Hailiang,DENG Ling,HU Changyu

DOI: 10.19585/j.zjdl.202411012

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