基于概率最优潮流的电力系统灵活性量化评估方法

A Quantitative Assessment Method for Power System Flexibility Based on Probabilistic Optimal Power Flow

可再生能源发电具有波动性和随机性,高比例可再生能源的接入给电力系统的灵活性带来挑战。为此,提出一种基于概率最优潮流的电力系统灵活性量化评估方法。首先,构建电力系统灵活性资源模型。采用k-means聚类方法处理历史数据以生成场景,基于马尔可夫链模型和Copula函数构建考虑时间相关性的风电、光伏出力及负荷波动概率模型。其次,将经济成本与系统灵活性关联,在考虑系统灵活性裕度期望、缺额期望和不足概率的基础上,建立计及运行经济性的量化评估指标。第三,构建含灵活性资源的概率最优潮流模型,采用蒙特卡罗模拟方法和基于跟踪中心轨迹内点法估计系统状态和评估指标。以IEEE RTS-24系统为算例进行分析,结果表明合理配置可再生能源和储能装置有助于提升系统灵活性和运行经济性。

Given its fluctuation and stochasticity,renewable energy generation’s high proportion to connect poses challenges to the flexibility of the power system.For that reason,a quantitative assessment method of power system flexibility based on probabilistic optimal power flow was proposed.Firstly,the flexible resource models of the power system were constructed.Historical data was processed to generate scenarios by using the k-means method,and the probabilistic models of wind power,photovoltaic power,and load fluctuation were constructed considering the time correlation based on the Markov chain model and the Copula function.Secondly,associating economic costs with system flexibility,quantitative assessment indicators that take into account the operational economy were established considering system flexibility margin expectations,vacancy expectations,and probability of deficiencies.Thirdly,the probabilistic optimal power flow model with flexibility resources was constructed,and the system state and index were estimated by the Monte Carlo simulation method and tracking center trajectory interior point method.Finally,analyzing the case of the IEEE RTS-24 system show that the appropriate allocation of renewable energy and energy storage systems could improve system flexibility and operating economy.