基于逐时气象信息的相似日回归模型夏季负荷预测
首发时间:2007-03-02
摘要:日负荷预测是电力市场运营的基本内容,预测精度高低对于电力系统安全经济调度运行具有极为重要的指导作用。如何提高预测精度也是学界一直不懈的追求目标。随着气象预报技术的发展及逐时预报技术的出现,电力部门尝试采用更为精确的逐时气象数据来预报对气象敏感的气象敏感负荷。针对短期负荷预测,作者通过分析郑州地区夏季日负荷数据与逐时气象数据,剖析了气象因素的影响和作用,提出了新的基于逐时气象数据选取相似日,根据夏季模式分类建立回归模型预测96点负荷的短期负荷预测方法,该模型力图寻求温度、湿度等逐时气象因素与负荷曲线之间的相关关系用于夏季天气多变的负荷预测。并用标准C语言编写程序嵌入电力市场软件UNIX环境下运行。实际应用表明,此预测模型取得了较好的预测效果。
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Regression modeling for summer short-term load forecasting based on hourly weather factors
Abstract: Short-term load forecasting is one of the basic operation of the electrical marketing, its forecasting precision make great significance to the secure and economic operation of power system and always be the pursuit target. With the development of weather forecasting technology and hourly weather factors’ occurrence, much more accurate hourly weather factors is preferred to forecast the load sensitive to meteorology. On short-term forecasting, by analyzing the historical data records of weather and load of Zhengzhou district, extracting the correlativity of main weather factors with load, the author proposed a regression modeling for summer short-term 96-point load forecasting, based on similar day on hourly weather factors and the corresponding summer load mode, and try to figure our correlativity of load curve with the hourly weather factors such temperature, humidity, rainfall and so on. This method is programmed with standard C language and embedded in electrical marketing software package in UNIX system, actual application shows better records.
Keywords: short-term load forecasting hourly weather factors, similar day multi-regression
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No.1125999428117280****
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