含光伏电站的电力系统概率潮流计算

发布时间：2018-12-11 12:35

【摘要】：近几年光伏发电得到了迅速的发展,其在电网中的渗透率逐渐提高。大力发展光伏发电对于国家的能源供应和能源安全具有重要的意义,是未来电力系统的发展趋势之一。但光伏发电受光照强度等气象条件影响非常大,这使得光伏输出功率具有很强的波动性。传统的确定性潮流很难评估系统运行的波动性,而概率潮流能够考虑光伏输出功率的波动性,并且还能考虑负荷的随机波动和常规发电机故障停运等情况。通过概率潮流计算得到各节点电压以及支路潮流的概率分布,为电力系统的运行规划、继电保护整定等提供重要的参考信息。传统的概率潮流采用半不变量法进行计算分析,并且要求节点输入量之间相互独立,而在实际情况下往往不能满足这个条件。地理位置较近的光伏发电系统,输出功率之间具有相关性,会对概率潮流计算的准确性产生影响。本文采用改进的Nataf变换处理光伏出力之间的相关性,并结合半不变量和C型Gram-Charlier级数进行概率潮流计算。该方法不仅较蒙特卡洛法有更高的计算效率,而且能够体现变量空间之间的变换过程,对于不服从正态分布的光伏出力之间的相关性具有较好的处理效果,同时C型Gram-Charlier级数可以防止概率密度值出现负值的情况。通过IEEE14节点算例和南方某地区实际电网算例验证了所提方法的有效性。
[Abstract]:In recent years, photovoltaic power generation has been rapid development, its permeability in the grid gradually increased. The development of photovoltaic power generation is of great significance to national energy supply and energy security, and is one of the development trends of power system in the future. However, photovoltaic power generation is greatly affected by meteorological conditions such as light intensity, which makes photovoltaic output power have strong volatility. The traditional deterministic power flow is difficult to evaluate the operating volatility of the system, while the probabilistic power flow can take into account the fluctuation of photovoltaic output power, as well as the random fluctuation of load and the failure outage of conventional generators. The probabilistic distribution of each node voltage and branch power flow is obtained by probabilistic power flow calculation, which provides important reference information for power system operation planning, relay protection setting and so on. The traditional probabilistic power flow is calculated and analyzed by semi-invariant method, and the nodal input is required to be independent of each other, but this condition is often not satisfied in practice. There is a correlation between the output power of photovoltaic power generation system, which will affect the accuracy of probabilistic power flow calculation. In this paper, the improved Nataf transform is used to deal with the correlation between photovoltaic forces, and the probabilistic power flow is calculated with semi-invariant and C-type Gram-Charlier series. This method not only has higher computational efficiency than Monte Carlo method, but also can reflect the transformation process between variable spaces, and has a better processing effect on the correlation between photovoltaic forces from normal distribution. At the same time, C-type Gram-Charlier series can prevent the probability density from negative. The effectiveness of the proposed method is verified by an example of IEEE14 node and an actual power grid in southern China.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM744

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