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文章摘要
城市电网总量负荷年最大值的双向预测方法
The bi-directional method for the annual maximum of totalload forecasting in urban network
Received:July 19, 2016  Revised:August 23, 2016
DOI:
中文关键词: 城市电网  负荷预测  双向预测  加权平均
英文关键词: urban power network  load forecasting  bi-directional prediction  weighted average
基金项目:城市电网空间负荷预测的新型理论架构及其关键技术研究
Author NameAffiliationE-mail
Li Ke Institute of economic and technical research of Henan electric power company like9@ha.sgcc.com.cn 
He Qian State Grid Zhengzhou Power Supply Company heqian4@ha.sgcc.com.cn 
Wang Jing Institute of economic and technical research of Henan electric power company wangjing22@ha.sgcc.com.cn 
Xiao Bai* School of Electrical Engineering,Northeast Dianli University xbxiaobai@126.com 
Liu Tongtong School of Electrical Engineering, Northeast Dianli University tttongtong2015@163.com 
Fang Longjiang School of Electrical Engineering, Northeast Dianli University vanloo@163.com 
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中文摘要:
      城市电网总量负荷预测是城市电网规划的基础工作。为了充分挖掘并利用负荷历史数据的更多信息,提出一种城市电网总量负荷年最大值的双向预测方法。该方法基于历史数据分析了电力负荷与用电量的相关关系,建立了负荷-用电比模型,据此求得基于用电量数据的各月电力负荷最大值,并利用这些最大值分别运用线性回归、指数平滑、灰色理论从纵向和横向对目标年的总量负荷最大值进行预测,将所得的六个预测值加权平均作为最终预测结果。实例分析表明该方法是正确的、有效的。
英文摘要:
      The total load forecasting of urban power network is the fundamental work of urban power network planning. In order to fully tap and use more information of load historical data, a bi-directional prediction method for the annual maximum of total load forecasting in urban network is proposed. The method analyzes of the correlation of power load and power consumption based on historical data, establishes the model of Load-electricity ratio, hereby obtains the power load maximum of each month by using power consumption data, and then forecasts the total load maximum of the objective years on the basis of these maximum from horizontal and vertical directions by using linear regression, exponential smoothing and gray theory, serves the weighted average value of the six predicted value as the Final predicted results. Example analysis shows that the method is correct and effective.
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