考虑气象条件下的电力系统短期负荷预测研究

【作者】 吴小明；

【导师】 邱家驹；

【作者基本信息】 浙江大学 ， 电气工程及其自动化， 2003， 硕士

【摘要】 电力系统负荷预测的水平已成为衡量电力系统运行管理现代化的标志之一。尤其是准确的短期负荷预测更是具有重要的意义。负荷预测的影响因素较多，既由负荷本身的历史表现决定，还要受众多非负荷因素的影响。非负荷因素中又以气象因素权重最大。 负荷坏数据辨识是由负荷曲线抗差聚类和坏数据曲线模式分类两个顺序的过程组成的；本文通过对Kohonen网的抗差聚类和BP网模式分类的效果分析，设计由这两种网络组合而成的神经网络模型，较好地完成了坏数据辨识的任务。 在正常日预测中，通过深入研究各个时段负荷和气象之间的变化关系，本文设计了一个由时间序列、模糊推理和一元回归修正模型组成的综合模型，在气温变化剧烈的季节利用一元回归模型对前两种模型进行修正，预测的结果表明了这种修正的有效性。考虑到节假日负荷中商业和居民用电比例高，本文结合相邻近的周末负荷考虑温度因素来对其进行预测。节后工作日预测的预测中则采用灰色预测模型，能用较少的历史数据通过累加生成推导其变化规律。 单一模型所用到的信息毕竟有限，各个模型所用到的信息不会完全相同，所以本文最后对各个单一模型的结果建立了EW组合预测模型，所有的建模和计算都是针对浙江省负荷数据的，据此开发的程序已经在浙江省电力调度中心得到了应用，达到了较高的准确率。更多还原

【Abstract】 The level of load forecasting is one of the measures of modernization of power system management. So load forecasting, especially accurate short-term load forecasting is of great importance to power system. There are many factors that affect system load, such as history data of load, many non-load factors in which weather factor is the most important.The outlier identification is divided into two sequential parts: the robust day-load-curves cluster and the bad curve pattern classification. By analyzing the effects of Kohonen network clustering and BP network classification, the dissertation designs an outlier identification model comprising these two kinds of neural network and implements the tasks of bad data identifications and adjustments.In order to forecast normal day load, this thesis advances a integrated model consisting of time series model, fuzzy model and linear regression model through studying the relations between load and weather; In order to forecast the load of such day which temperature change sharply, this thesis uses the 3r model to adjust the former two models and the forecasting results validate the effectivity of the adjustment; In order to forecast festal day load, this thesis uses the neighboring weekends load data while considering temperature factor and uses gray model to forecast the load of the day after the feast.A single model can only make use of limited information and the information that the models used can’t be the completely same, so a EW integrated forecasting model is proposed in the end of the thesis to improve the accurateness. All modeling and forecasting are based on the data of Zhejiang province load and the program is applied in the power dispatch center of Zhejiang province and it’s performance is satisfactory.更多还原