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基于Gram-Charlier 级数的含风电电力系统静态电压稳定概率评估 被引量:15

Probabilistic evaluation of power system static voltage stability with wind power uncertainty based on the Gram-Charlier expansion
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摘要 可再生能源的波动性和随机性加剧了传统电力系统静态电压稳定评估的难度。为了有效计及风电出力不确定性对静态电压稳定评估的影响,提出了一种计及风电出力不确定性的静态电压稳定概率评估方法。首先,借助电力系统负荷裕度,推导各节点负荷裕度对风电注入功率的灵敏度,进而求解负荷裕度的各阶半不变量和负荷裕度的各阶矩。然后,结合风电所连节点注入功率的各阶矩和半不变量,对负荷裕度各阶矩进行Gram-Charlier展开,以求取计及风电不确定性的负荷裕度概率分布,进而实现电力系统静态电压稳定概率评估。最后,通过IEEE30节点系统验证所提方法的准确性和有效性。 The volatility and randomness of renewable energy have exacerbated the difficulty of evaluating static voltage stability in traditional power systems.In order to effectively account for the impact of wind power output uncertainty on static voltage stability assessment,first,the sensitivity of each node load margin to wind power injection power is derived through the power system load margin.Further,each order semi-invariant and each order moment of power system load margin are determined.Then,combining the various moments and semi-invariants of the injected power of the nodes connected to the wind power,the Gram-Charlier expansion of the various moments of the load margin is carried out.Thus the probability distribution of the load margin is obtained by taking into account the uncertainty of wind power to realize the probability assessment of the static voltage stability of the power system.Finally,the accuracy and effectiveness of the proposed method are verified by the IEEE30 node system.
作者 那广宇 魏俊红 王亮 王长江 NA Guangyu;WEI Junhong;WANG Liang;WANG Changjiang(State Grid Liaoning Electric Power Co.,Ltd.,Shenyang 110006,China;Huadian Electric Power Research Institute,Shenyang 110167,China;School of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China)
出处 《电力系统保护与控制》 EI CSCD 北大核心 2021年第3期115-122,共8页 Power System Protection and Control
基金 国网辽宁省电力限公司科技项目资助“辽宁电网采用新能源主动支撑技术的稳定性研究”(2018YF-25) 国家电网有限公司科技项目资助“千万千瓦级分层接入直流送受端系统动态行为机理和协调控制措施研究”(SGTYHT17-JS-199)。
关键词 负荷裕度 Gram-Charlier 静态电压稳定 半不变量法 load margin Gram-Charlier steady-state voltage stability semi-invariant method
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