文章摘要
吴俊,薛禹胜,舒印彪,等.大规模可再生能源接入下的电力系统充裕性优化:(一)旋转级备用的优化[J].电力系统自动化,2019,43(8):101-109. DOI: 10.7500/AEPS20181023001.
WU Jun,XUE Yusheng,SHU Yinbiao, et al.Adequacy Optimization for a Large-scale Renewable Energy Integrated Power System Part One Spinning-grade Reserve Optimization[J].Automation of Electric Power Systems,2019,43(8):101-109. DOI: 10.7500/AEPS20181023001.
大规模可再生能源接入下的电力系统充裕性优化:(一)旋转级备用的优化
Adequacy Optimization for a Large-scale Renewable Energy Integrated Power System Part One Spinning-grade Reserve Optimization
DOI:10.7500/AEPS20181023001
关键词: 可再生能源  电力系统旋转级备用  合约优化  代价性能比  机组组合
KeyWords: renewable energy  power system spinning-grade reserve  contract optimization  cost-performance ratio  unit commitment
上网日期:2019-03-19
基金项目:国家电网公司科技项目“电力转型对能源转型的主动支撑研究——以青海省为例”;国家自然科学基金资助项目(61533010);国电南瑞集团有限公司科技项目“综合能源系统仿真评估关键技术研究”
作者单位E-mail
吴俊 南京理工大学自动化学院, 江苏省南京市 210094
南瑞集团有限公司(国网电力科学研究院有限公司), 江苏省南京市 211106 
 
薛禹胜 南瑞集团有限公司(国网电力科学研究院有限公司), 江苏省南京市 211106
南京理工大学自动化学院, 江苏省南京市 210094 
xueyusheng@sgepri.sgcc.com.cn 
舒印彪 国家电网有限公司, 北京市 100031  
谢东亮 南瑞集团有限公司(国网电力科学研究院有限公司), 江苏省南京市 211106  
薛峰 南瑞集团有限公司(国网电力科学研究院有限公司), 江苏省南京市 211106  
许剑冰 南瑞集团有限公司(国网电力科学研究院有限公司), 江苏省南京市 211106  
摘要:
      大规模可再生能源接入需要及时响应的各级备用容量支撑,合理配置立即可用的旋转级发电侧和需求侧备用容量对平衡系统可靠性与经济性至关重要。建立有偿使用备用服务的市场机制,其基本任务是购入合适的备用容量,在满足潜在风险场景下调度需求的同时,降低系统总成本。这就要求:考察每个可选备用措施(RM)在风险场景下的备用价值;从中选取性价比较高的RM或其组合。三篇连载文章完成了场景集下多等级备用协调优化的具体建模与求解,作为连载的第一篇,文中在分析现有备用优化求解方法的基础上,提出了基于RM代价性能比的旋转级备用优化方法。以穷尽式寻优方法为精度基准,通过所提方法与混合整数线性规划方法的对比,验证了所提方法的有效性。同时通过算例,从效率和精度两个方面给出了所提优化方法在不同规模系统下的表现。
Abstract:
      Large-scale renewable energy generation connected to the grid requires support from system reserve capacity with immediate response of all grades. Wise allocation of instant spinning-grade reserve on the generation and demand side becomes a vital mission to balance the reliability and economy of power system. The core task of a market which encourages non-free use of reserve capacity is to purchase proper reserve capacity and reduce the total cost of the system by satisfying dispatch needs of all potential risk scenarios. To achieve this, the reserve values of every available reserve measure(RM)under all risk scenarios are estimated, and RMs or their combinations with high performance cost ratio are selected. Three series articles present a novel way to model and solve the multi-grade reserve optimization problem considering variant scenarios. As the first article in the series, on the basis of analyzing existing reserve optimization methods, a cost-performance ratio based spinning-grade reserve optimization method is proposed. Using the exhaustively searching method as the benchmark, the effectiveness of the proposed method is verified by comparing with the mixed-integer linear programming method. Simulation cases on systems with different scales also give the general picture about the efficiency and accuracy of the proposed method relative to its main competitors.
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