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风险量化的高比例新能源电力系统概率调度 被引量:4

Risk-Quantified Probabilistic Dispatch for Power System with High Proportion of Renewable Energy
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摘要 新能源大规模并网给电力系统的运行带来重大技术挑战,传统确定性调度模式缺乏对不确定性条件下的安全风险量化管控,而鲁棒优化调度过于保守。基于随机优化的概率调控技术具有风险可控、统计最优性等特点,但是存在概念与内涵不清、概率建模困难、复杂机会约束模型求解低效等问题,概率调度技术的实际应用面临困难。为此,提出了风险量化的概率调度定义与技术内涵,阐释了处理新能源发电不确定性所遵循的基本原理,然后重点介绍了如下概率调度的关键技术:1)新能源概率建模的数学基础;2)概率备用决策与机组组合;3)考虑弃电与有序用电的概率日前调度计划;4)随机鲁棒自适应实时调度。最后,简要分析了所提方法在省级电网的应用效果,并对后续的研究进行了展望。 The large-scale integration of renewable energy has brought great technical challenges to the operation of power systems.The traditional deterministic dispatch modes ignore the quantification management of safety risks under uncertainties.While,the robust optimal dispatch is over-conservative.The probabilistic dispatch and control technique based on the stochastic optimization has the characteristics of risk controllability and statistical optimality.However,there are problems such as unclear concepts and connotations,difficulties in probabilistic modeling,and low efficiency in solving the complex chance constrained models.The practical application of the probabilistic dispatch technique faces difficulties.Therefore,the definition and technical connotation of risk-quantified probabilistic dispatch are proposed,and the followed basic principles in dealing with the uncertainty of the renewable energy are illustrated.Then the key techniques of risk-quantified probabilistic dispatch are stressed,which include:1)mathematical basis for probabilistic modeling of the renewable energy;2)probabilistic reserve decision and unit commitment;3)probabilistic dayahead dispatch considering renewable energy curtailment and orderly power utility;4)stochastic robust adaptive real-time dispatch.Finally,the application effects of the proposed method in provincial power grids are briefly analyzed,and the future research topics are prospected.
作者 吴文传 许书伟 杨越 王彬 蔺晨晖 沈宇康 WU Wenchuan;XU Shuwei;YANG Yue;WANG Bin;LIN Chenhui;SHEN Yukang(Department of Electrical Engineering,Tsinghua University,Beijing 100084,China;State Key Laboratory of Power System Operation and Control(Tsinghua University),Beijing 100084,China;School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 230009,China;Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving(Hefei University of Technology),Hefei 230009,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2023年第15期3-11,共9页 Automation of Electric Power Systems
基金 广东省重点领域研发计划资助项目(2021B0101230004) 国家自然科学基金资助项目(51725703)。
关键词 高比例新能源 高斯混合模型 概率备用决策 机组组合 概率调度 随机鲁棒实时调度 high proportion of renewable energy Gaussian mixture model probabilistic reserve decision unit commitment probabilistic dispatch stochastic robust real-time dispatch
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