| 引用本文: | 陈厚合,王杨,张儒峰,郭放,贾蒙,孙东方.考虑源荷协调的风电并网系统旋转备用容量优化[J].电力自动化设备,2017,37(8): |
| CHEN Houhe,WANG Yang,ZHANG Rufeng,GUO Fang,JIA Meng,SUN Dongfang.Spinning reserve capacity optimization considering coordination between source and load for power system with wind power[J].Electric Power Automation Equipment,2017,37(8): |
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| 摘要: |
| 风电的接入给电力系统带来更大不确定性，要求电网公司购买更多的旋转备用以维持电力系统的功率平衡和稳定，兼顾系统运行可靠性与经济性的旋转备用优化配置具有重要意义。考虑风电、需求侧互动资源，提出一种基于多场景的概率性旋转备用优化方法。该方法综合考虑风电预测误差、负荷波动及发电机非计划停运不确定性因素对旋转备用的需求，将弃风、可中断负荷分别作为部分负、正旋转备用融入发电日前调度计划，以购电总费用最低为目标函数建立日前机组组合优化模型，获得各时段旋转备用优化配置量。通过对IEEE 30节点、IEEE 118节点系统进行算例分析，验证了所提方法的正确性和有效性。 |
| 关键词: 风电 弃风 可中断负荷 旋转备用 机组组合 |
| DOI：10.16081/j.issn.1006-6047.2017.08.025 |
| 分类号:TM761;TM614 |
| 基金项目:国家自然科学基金资助项目(51377016,51477027, 5167070297, 51607033,51607034) |
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| Spinning reserve capacity optimization considering coordination between source and load for power system with wind power |
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CHEN Houhe1, WANG Yang1, ZHANG Rufeng1, GUO Fang2, JIA Meng3, SUN Dongfang4
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1.School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China;2.Department of Power Engineering, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China;3.Beijing Jingneng Future Gas Thermal Power CO.,LTD.,Beijing 102200, China;4.State Grid Zhejiang Haining Power Supply Company, Jiaxing 314400, China
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| Abstract: |
| Since the integration of wind power brings more uncertainties to power system and asks the power grid companies to buy more spinning reserve for maintaining the power balance and stability of power system, the spinning reserve optimization considering both operational reliability and economics of power system is very significant. A method of multi-scenario-based probabilistic spinning reserve optimization considering the interactive resources of wind power and demand side is proposed, which thinks comprehensively about the spinning reserve demands due to the uncertainties of wind power forecasting error, load fluctuation and unscheduled unit outage, integrates the wind power curtailment and the interruptible load as part negative and positive spinning reserves respectively into the day-ahead power generation scheduling, and takes the minimum total electricity purchasing cost as the objective to build a day-ahead unit commitment optimization model for obtaining the optimal spinning reserve capacity of each period. Case analysis on IEEE 30-bus system and IEEE 118-bus system demonstrates the correctness and effectiveness of the proposed method. |
| Key words: wind power wind power curtailment interruptible load spinning reserve unit commitment |
