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1. 广东电网有限责任公司电网规划研究中心,广东省 广州市 510080
2. 广东电网有限责任公司,广东省 广州市 510620
程鑫(1987—),男,通信作者,硕士,高级工程师,主要研究方向:能源与电力发展规划、电网规划、储能应用等。E-mail:flyerinsky@foxmail.com
许亮(1987—),男,硕士,工程师,主要研究方向:电力系统规划、大规模海上风电输电。E-mail:xuliang-27@163.com
周姝灿(1990—),女,硕士,工程师,主要研究方向:电力系统规划。E-mail:zsc_1990@126.com
收稿日期:2019-07-17,
修回日期:2019-09-20,
网络出版日期:2020-02-16,
纸质出版日期:2020-07-10
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程鑫,许亮,周姝灿等.基于新能源出力保证率轨迹灵敏度分析的储能配置方法[J].电力系统自动化,2020,44(13):25-31.
CHENG Xin,XU Liang,ZHOU Shucan,et al.Energy Storage Configuration Method Based on Trajectory Sensitivity Analysis of Output Guaranteed Rate for Renewable Energy[J].Automation of Electric Power Systems,2020,44(13):25-31.
程鑫,许亮,周姝灿等.基于新能源出力保证率轨迹灵敏度分析的储能配置方法[J].电力系统自动化,2020,44(13):25-31. DOI: 10.7500/AEPS20190717008.
CHENG Xin,XU Liang,ZHOU Shucan,et al.Energy Storage Configuration Method Based on Trajectory Sensitivity Analysis of Output Guaranteed Rate for Renewable Energy[J].Automation of Electric Power Systems,2020,44(13):25-31. DOI: 10.7500/AEPS20190717008.
大规模新能源接入电网使得电源出力的不确定性超过了负荷需求的不确定性,电力系统概率潮流加大了运行部门的管理难度。针对这一问题,提出了一种基于新能源出力保证率轨迹灵敏度分析的储能配置方法。首先根据新能源出力的不确定性,建立了受考核元件的概率潮流越限方程。其次,以新能源出力保证率作为参数改变量,建立概率潮流的轨迹灵敏度分析模型。然后,提出了使得概率潮流不发生越限储能容量配置策略,针对轨迹灵敏度较小的元件相关节点,计算储能功率需求和储能能量需求。最后,在中国南方某地区实际电力系统进行了算例仿真,验证了所提方法的有效性。
The integration of large-scale renewable energy to the power grid makes the uncertainty caused by power supply higher than the uncertainty of load demand. The probabilistic power flow of power system makes the management of operation department even more difficult. To solve this problem
this paper proposes an energy storage configuration method based on trajectory sensitivity analysis of guaranteed rate for renewable energy output. Firstly
an over-limit equation of probabilistic power flow for assessed components is set up according to the uncertainty of new energy output. Secondly
an analysis model of trajectory sensitivity for probabilistic power flow is built by setting the guaranteed rate of new energy output as a parameter. Thirdly
a configuration strategy of energy storage is proposed to make the probabilistic power flow not exceed limit. Meanwhile
power and energy requirements of energy storage are calculated for component-related nodes which have low trajectory sensitivities. Finally
the proposed method is simulated and verified on a practical power system in an area of South China.
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