摘要
随着风电接入电网的比例不断提高,风电的不确定性对电力系统的运行调度提出了严峻挑战。将满足一定置信水平的风电区间预测信息纳入到日前调度计划中有助于提高系统的安全性和经济性。为此提出了基于风电区间预测信息的随机安全约束机组组合模型(stochastic security-constrained unit commitment,SSCUC)。该模型将风电的不确定性用1个确定的预测风电场景和2个极限风电场景来表示,简化了问题的复杂度。同时,该模型引入了潮流约束和网络安全约束,保证了调度结果的可行性。为求解该模型,提出了基于广义Benders分解的计算方法。该方法将SSCUC问题分解为一个主问题和2T(T为调度周期)个约束潮流子问题,并通过交替迭代的方式获得原问题的最优解。4机9节点系统和改进118节点系统的计算结果验证了所提模型和算法的有效性。
With increasing integration of wind farms, uncertainty of wind power brings severe challenges to power system scheduling and operation. It is helpful to incorporate wind power interval prediction information into day-ahead scheduling for improving system security and economy. A new stochastic-security-constrained unit commitment（SSCUC） model based on wind power interval prediction is proposed. This model simplifies complexity of the problem by representing wind power uncertainty with a deterministic wind power scenario and two extreme wind scenarios. In addition, the model introduces power flow and network security constraints to ensure feasibility of scheduling results. In order to solve this problem, a method based on generalized Benders decomposition is proposed. This method decomposes SSCUC problem into a master problem and 2T constrained power flow sub problems, and obtains optimal solution of original problem by alternating iterations. Results of a 4-unit 9-bus test system and a modified 118-bus test system show effectiveness of the proposed model and algorithm.
出处
《电网技术》
EI
CSCD
北大核心
2017年第5期1419-1427,共9页
Power System Technology
基金
国家重点基础研究发展计划项目(9 7 3项目)(2013CB228205)
国家自然科学基金项目(51667003)~~
关键词
机组组合
风电
不确定性
区间预测
安全约束
广义Benders分解
unit commitment
wind power
uncertainty
interval prediction
security constraints
generalized Benders decomposition
