文章摘要
陈佳佳,赵艳雷,亓宝霞,等.计及风电预测误差的电力系统风险规避评估模型[J].电力系统自动化,2019,43(3):163-168. DOI: 10.7500/AEPS20180119008.
CHEN Jiajia,ZHAO Yanlei,QI Baoxia, et al.Assessment Model of Risk Aversion for Power System Considering Wind Power Forecasting Error[J].Automation of Electric Power Systems,2019,43(3):163-168. DOI: 10.7500/AEPS20180119008.
计及风电预测误差的电力系统风险规避评估模型
Assessment Model of Risk Aversion for Power System Considering Wind Power Forecasting Error
DOI:10.7500/AEPS20180119008
关键词: 概率区间优化  不确定风电  预测误差  风险规避模型  优化调度
KeyWords: probability interval optimization (PIO)  uncertain wind power  forecasting error  risk aversion model  optimal dispatch
上网日期:2018-12-25
基金项目:国家重点研发计划资助项目(2017YFB0902800);山东省自然科学基金资助项目(ZR2016EEQ21)
作者单位E-mail
陈佳佳 山东理工大学电气与电子工程学院, 山东省淄博市 255049 jjchen@sdut.edu.cn 
赵艳雷 山东理工大学电气与电子工程学院, 山东省淄博市 255049  
亓宝霞 山东理工大学电气与电子工程学院, 山东省淄博市 255049  
刘伟 山东理工大学电气与电子工程学院, 山东省淄博市 255049  
摘要:
      风电功率的短时大幅波动对电网的安全稳定运行造成冲击,为更准确地评估电力系统在较短时间内的风电消纳情况,需考虑风电功率的预测误差。为此,文中提出一种概率区间优化模型,从效益和风险两个维度评估风电预测误差对电力系统运行的影响,旨在得到最优权衡风险和效益的调度方案。在概率区间优化模型中,不确定风电被视为概率区间变量,即每个风电值对应一个分布概率。效益用不确定风电并网前后系统运行费用的差值来量度;风险则用风电的分布概率来衡量。然后,构建基于效益和风险的条件期望作为优化目标。最后,在一个调度系统上进行仿真并与区间优化模型对比,证明了所提出的优化模型的可靠性、鲁棒性和实用性。
Abstract:
      The large fluctuation of short-term wind power brings significant challenges to power grid operation in terms of stability and security. In order to accurately assess the wind power accommodation of power systems in a short period, it is necessary to consider the forecasting error. In view of this, this paper proposes a probability interval optimization (PIO) model to evaluate the impact of wind power forecasting error on power system operation from the perspective of profit and risk, which aims to obtain the optimal dispatch scheme considering both profit and risk. In the PIO model, the uncertain wind power is formulated as a probability interval variable, i.e., each wind power corresponds to a distribution probability. The profit is measured by the difference of operation cost between the same power system with and without the integration of wind power, and the risk is assessed by the distribution probability of wind power. Then the optimization objective is formulated as the conditional expectation with respect to profit and risk. Finally, numerical results are conducted in a dispatch system to compare the performance of the proposed model with the interval optimization model. The reliability, robustness and applicability of the proposed model is verified.
查看全文(Free!)   查看附录   查看/发表评论  下载PDF阅读器