| 引用本文: | 肖逸,谢俊,刘若平,李银红.计及风电功率预测误差的备用容量计算新方法[J].电力系统保护与控制,2019,47(9):72-79.[点击复制] |
| XIAO Yi,XIE Jun,LIU Ruoping,LI Yinhong.A new calculation method of reserve capacity considering wind power forecasting error[J].Power System Protection and Control,2019,47(9):72-79[点击复制] |
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| 摘要: |
| 风电出力的不确定性对于备用容量的配置具有重要影响。基于此，提出了一种计及风电功率预测误差的备用容量计算新方法。针对拉普拉斯分布形状调整不够灵活的问题，提出了一种改进拉普拉斯分布。并以此为基础，提出了一种发电机备用容量计算新方法。该方法首先以最小化发电成本为目标的最优潮流模型，对系统各机组的运行基准点进行求解；再按照鲁棒优化思想并结合发电机自动发电控制(AGC)的仿射模型建立鲁棒最优潮流模型求解各AGC机组参与因子；最后结合等概率转换原则求解系统的备用容量。算例分析表明，所提改进拉普拉斯分布模型拟合效果较好，且所提备用容量计算新方法能够综合考虑系统安全性和经济性的需求。 |
| 关键词: 预测误差 改进拉普拉斯分布 备用容量 仿射模型 鲁棒最优潮流 |
| DOI：10.7667/PSPC180677 |
| 投稿时间：2018-06-04修订日期：2018-07-29 |
| 基金项目:国家重点研发计划支持项目(2016YFB0900100) |
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| A new calculation method of reserve capacity considering wind power forecasting error |
| XIAO Yi,XIE Jun,LIU Ruoping,LI Yinhong |
| (State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology, Wuhan 430074, China;Central China Branch of State Grid Corporation, Wuhan 430077, China) |
| Abstract: |
| The uncertainty of wind power has great influence to spare capacity. On this basis, a new calculation method of spare capacity considering wind power forecasting error is proposed. Firstly, considering the inflexible problem of Laplace distribution, an improved Laplace distribution is proposed. Secondly, a new method is proposed to calculate the spinning reserve capacity. First, taking minimum cost as objective function, the based operation point can be gotten by solving the optimal power flow. Then, it builds robust optimal power flow model by considering robust optimization and affine model of Automatic Generation Control (AGC) to solve the participation factors of AGC generators. The spare capacity can be solved combining equal probability conversion principle. From the simulation, the proposed forecasting error model is of high accuracy and the calculation satisfies the requirements of safety and economy. This work is supported by National Key Research and Development Program of China (No. 2016YFB0900100). |
| Key words: forecasting error improved Laplace distribution spare capacity affine model robust optimal power flow |
