计及不确定性的新型灵活性资源两阶段鲁棒配置优化模型OA北大核心CSTPCD
Optimal Two-Stage Robust Configuration Model and Algorithm of New Flexibility Resources Considering Uncertainty
随着新能源在电力系统中的占比不断提高,新型电力系统的安全稳定运行受到极大的挑战,亟待进行新型灵活性资源容量配置.为此,计及新能源出力不确定性,构建一种考虑灵活性需求约束的两阶段鲁棒容量优化配置模型.首先,针对风光等新能源的不确定性特征,对电力系统的灵活性需求进行刻画,分析灵活性资源调节特性,对新型灵活性资源的调节能力进行建模.然后,引入不确定性参数,建立一种考虑灵活性供需平衡的两阶段鲁棒容量优化配置模型,基于列与约束生成(column-and-constraint generation,C&CG)算法与KKT定理,求解系统对应的最优规划结果.最后,选取我国某地电力系统为仿真对象进行实证分析,验证所构建模型的有效性.算例结果表明,所构建的两阶段鲁棒配置优化模型可以应对电力系统的不确定情况与新能源带来的灵活性需求,规划结果能够在新型电力系统的安全性与经济性上达成平衡.
The safe and stable operation of new power systems has become challenging,with the increasing proportion of new energy sources in power systems.Configuring new,flexible-resource capacities has become urgent.This study considers the uncertainty in the new energy output and constructs an optimal,two-stage,robust,configuration model that considers flexibility-demand constraints.The flexibility demand of the power system is modelled with respect to the uncertainty characteristics of new energy sources,such as wind power and photovoltaic(PV)power;the regulation characteristics of new flexibility resources are analyzed to model their regulation capacity;uncertainty parameters were introduced to establish a two-stage,robust,capacity optimization model considering the balance of flexible supply and demand,and the corresponding optimal planning results of the system were solved based on the CCG algorithm and the KKT theorem.The power system of a certain location in China was selected as the simulation object for empirical analysis to verify the validity of the constructed model.The results show that the optimal,two-stage,robust,configuration model constructed in this study can effectively cope both with the uncertainty of the power system and the flexibility demand brought about by new energy sources.A balance between the security and economy of the new power system can be planned.
朱海军;鞠立伟;杨慧;齐鑫;瞿斌
华北电力大学经济与管理学院,北京市 102206
动力与电气工程
新型灵活性资源配置模型不确定性两阶段鲁棒优化
new flexibility resourceconfiguration modeluncertaintytwo-stage robust optimization
《电力建设》 2024 (007)
1-11 / 11
This work is supported by State Grid Corporation of China Headquarter Management Science and Technology Project(No.1400-202224249A-1-1-ZN). 国家电网有限公司总部管理科技项目资助(1400-202224249A-1-1-ZN)
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