| 引用本文: | 谢敏,罗文豪,吉祥,程培军,柯少佳,刘明波.随机风电接入的电力系统动态经济调度多场景协同优化[J].电力自动化设备,2019,39(11): |
| XIE Min,LUO Wenhao,JI Xiang,CHENG Peijun,KE Shaojia,LIU Mingbo.Multi-scenario collaborative optimization for dynamic economic dispatch of power system with stochastic wind power integration[J].Electric Power Automation Equipment,2019,39(11): |
|
| 摘要: |
| 针对随机风电接入的电力系统动态经济调度问题，采用场景法应对随机风电接入带来的不确定性，并以发电总成本最小为优化目标，结合多学科协同优化算法的核心思想建立基于多场景解耦的电力系统动态经济调度协同优化模型。引入动态松弛算法求解模型的系统级优化问题，有效克服传统多学科协同优化算法的不足；采用网格计算工具并行求解由多场景构建的子学科优化问题，大幅提高求解规模和计算效率。含风电的IEEE 39节点系统仿真结果表明，所提模型是可行有效的，并且优化效果要优于基于GAMS-BARON求解器的传统场景法。 |
| 关键词: 风电 动态经济调度 场景法 多学科协同优化 动态松弛算法 |
| DOI：10.16081/j.epae.201910008 |
| 分类号:TM73;TM614 |
| 基金项目:广东省自然科学基金自由申请项目(2018A0303-130134) |
|
| Multi-scenario collaborative optimization for dynamic economic dispatch of power system with stochastic wind power integration |
|
XIE Min1, LUO Wenhao2, JI Xiang3, CHENG Peijun4, KE Shaojia5, LIU Mingbo1
|
|
1.School of Electric Power, South China University of Technology, Guangzhou 510640, China;2.Foshan Power Supply Bureau of Guangdong Power Grid Corporation, Foshan 528000, China;3.State Grid Jiaxing Power Supply Company, Jiaxing 314033, China;4.Guangzhou Power Supply Bureau Co.,Ltd.,Guangzhou 510600, China;5.State Grid Fuzhou Power Supply Company, Fuzhou 350009, China
|
| Abstract: |
| Aiming at the dynamic economic dispatch problem of power system integrated with stochastic wind power, the scenario method is adopted to deal with the uncertainties brought by the integration of wind power, and combined with the core idea of MCO(Multidisciplinary Collaborative Optimization),a collaborative optimization model for dynamic economic dispatch of power system is built based on multi-scenario decoupling, which takes the minimum total generation cost as its optimization objective. The dynamic relaxation algorithm is introduced to solve the system-level optimization problem of the model, which effectively overcomes the shortcomings of traditional MCO. The grid computing tools are used to solve the sub-disciplinary optimization problems constructed by multi-scenario in parallel, which greatly improves the solution scale and computational efficiency. The simulative results of IEEE 39-bus system with wind power show that the proposed model is feasible and effective, and the optimization effect is superior to the traditional scenario method based on GAMS-BARON solver. |
| Key words: wind power dynamic economic dispatch scenario method multidisciplinary collaborative optimization dynamic relaxation algorithm |
