| 引用本文: | 温泽之,彭春华,孙惠娟.计及风电置信风险成本的多目标最优潮流计算[J].电力系统保护与控制,2020,48(24):36-43.[点击复制] |
| WEN Zezhi,PENG Chunhua,SUN Huijuan.Multi-objective optimal power flow calculation considering wind power confidence risk cost[J].Power System Protection and Control,2020,48(24):36-43[点击复制] |
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| 计及风电置信风险成本的多目标最优潮流计算 |
| 温泽之,彭春华,孙惠娟 |
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| (华东交通大学电气与自动化工程学院，江西 南昌 330013) |
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| 摘要: |
| 风电并网不确定性给电力系统最优潮流带来的风险性难以评估。首先基于风电机会约束概率提出了风电的高估/低估置信风险成本计算方法。然后计及风电置信风险成本构建了经济/环境多目标最优潮流模型，并提出了一种基于非劣性排序的复合回溯搜索(NSCBS)算法，以实现对多目标最优潮流模型高效准确的求解。最后以IEEE30节点为例进行计及风电置信风险成本的多目标最优潮流计算。结果验证了所提出方法的有效性和优越性。 |
| 关键词: 风电 机会约束 置信风险 多目标最优潮流 回溯搜索算法 |
| DOI：DOI: 10.19783/j.cnki.pspc.200219 |
| 投稿时间：2020-03-05修订日期：2020-05-01 |
| 基金项目:国家自然科学基金项目资助(51867008)；江西省自然科学基金项目资助(20192ACBL20007)；江西省教育厅科技项目资助(GJJ1903013) |
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| Multi-objective optimal power flow calculation considering wind power confidence risk cost |
| WEN Zezhi,PENG Chunhua,SUN Huijuan |
| (School of Electrical & Automation Engineering, East China Jiaotong University, Nanchang 330013, China) |
| Abstract: |
| In view of the difficulty in assessing the risks brought by the uncertainty of grid-connected wind power to the optimal power flow of the power system, a calculation method of overestimate/underestimate confidence risk cost for wind power based on the probability of a wind power opportunity constraint is proposed. Then, a multi-objective optimal power flow model for an environment/economy is established in consideration of wind power confidence risk cost, and a Non-Dominated Sorting Compound Backtracking Search (NSCBS) algorithm is proposed to achieve an efficient and accurate solution for the multi-objective optimal power flow model. Finally, a modified IEEE30-bus test system is taken as an example to calculate the multi-objective optimal power flow considering wind power confidence risk cost. The results verify the effectiveness and superiority of the proposed method.
This work is supported by National Natural Science Foundation of China (No. 51867008), Natural Science Foundation of Jiangxi Province (No. 20192ACBL20007) and Science and Technology Project of Jiangxi Province Education Department (No. GJJ1903013). |
| Key words: wind power opportunity constraint confidence risk multi-objective optimal power flow backtracking search algorithm |
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