【作者】 刘熙哲；

【导师】 周任军；

【作者基本信息】 长沙理工大学 ， 电力系统及其自动化， 2011， 硕士

【摘要】 电力负荷预测对于整个电力系统的运行与控制起着至关重要的作用,无论是经济调度、水火电协调还是发电计划的制定都是以负荷预测的数据为基础的。近年来随着风力发电、小型燃气轮机发电等新型发电方式的出现,以此为代表的分布式电源使传统的发、输电模式发生了巨大的变化。随着电网结构越来越复杂,以及电网规模的迅速扩大,系统对于电网稳定性的要求也不断提高,因此对负荷预测问题也提出了更新更有特点的要求。但在实际中取得的负荷数据中由于测量设备的误差、采样时间和地点的差异性等因素的影响,电力负荷时间序列呈现出复杂性、非线性、不确定性的特点。正是这些特点使得常规的预测方法无法很好的对含分布式电源的电系统负荷序列进行预测。由于混沌被认为是解决确定性的非线性系统中出现的具有内在随机性的解的有效方法。混沌时间序列的奇怪吸引子中包含了丰富的动力学信息,从有限的时间序列中就可以恢复出包含整个系统动力学特征的奇怪吸引子。因此混沌方法被认为是研究非线性时间序列的动力学特征的最好方法。本文从时间序列的相空间重构出发,利用MATLAB数学工具,采用功率谱方法和最大Lyapunov指数法研究含分布式电源的电力负荷时间序列的混沌性。并通过绘制时间序列的功率谱图和计算时间序列的离散卷积积分,探讨了确定相空间重构的嵌入维数和延迟时间参数的不同方法,并首次将一种改进的C-C算法引入到电力负荷时间序列的相空间重构参数的选取中。从定量的角度,分析了采用不同的时间序列预测方法对同一序列进行预测时产生的不同精度的预测结果,以及同一方法对不同时间序列进行预测时产生的结果在精度上的差异性。通过算例发现混沌方法得出的负荷预测结果的预测精度令人满意。更多还原

【Abstract】 The power load forecasting plays a vital role in the whole operation and control in electrical power system. Economic dispatch, hydro-thermal power coordination and power generation plan are all based on the load forecasting data. In recent years, with the arising of wind power generation, micro turbine generating and other new generating methods, distributed generators has greatly changed the traditional generation mode and transmission mode of power grid. The structure of power network becomes more and more complex and the scale continues to expand, which constantly raises the demand of power system stability. The accurate power load forecasting data can provide a solid protection for grid planning, scheduling and controlling. Because there are many influencing factors, the power load time series are complexity, nonlinearity and uncertainty. Because of these features, the load sequence is not accurately predicted by the conventional methods.Chaos is considered as an effective method of solving inherent randomness solution which in the deterministic nonlinear system. The strange attractors of chaos time series contain abundant dynamics information, and recover the chaos attractors with dynamic characteristic in the limited time series. Therefore, the chaos method is known as the best way of researching dynamics characteristic of the nonlinearity time series. Proceed from the phase space reconstruction of time sequence, this test makes use of the MATLAB, adopts power spectrum and maximum Lyapunov exponent to research the chaos of electric power system load time series which containing distributed generators, and discusses embedded dimensions of determining phase space reconstruction and different ways for delaying time parameters. Moreover, the modified C-C algorithm is introduced to the parameter selection of phase space reconstruction’s power load time series for the first time. From the quantitative angle, when adopting different ways of time series forecasting predict the same time series, it will bring out different predicting precision; on the contrary, when adopting the same way of time series forecasting predicts different time series, it will bring out differences in the predicting precision. According to the calculations, the prediction accuracy of load predicting by the chaos method is satisfactory.更多还原