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Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model

机译:基于指数平滑模型的节能监控平台电力消耗预测

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With the development of computer technology and Internet technology, more and more energy saving monitoring and management platform systems have been established. The energy saving monitoring and management platform has incomparable advantages in automation and real-time performance compared with traditional manual management. After a long time of operation, the energy saving monitoring and management platform has accumulated a lot of data. Due to various reasons, there is a lack of data in the process of collecting energy consumption, which affects the overall operation effect of the system. Based on the operation of an energy saving monitoring and management platform in a university in north China, this paper analyzes the data of building power consumption accumulated in recent years. This paper selects the typical metering branch data, establishes the exponential smoothing model, predicts the daily power consumption and analyzes the prediction results compared with the actual value to verify the effect of the prediction model. At the same time, it also provides a reference for the data prediction of energy conservation supervision platform of other universities.
机译:随着计算机技术和互联网技术的发展,已经建立了越来越多的节能监控和管理平台系统。与传统的手动管理相比,节能监控和管理平台在自动化和实时性能方面具有无与伦比的优势。经过长时间的操作,节能监控和管理平台积累了大量数据。由于各种原因,收集能耗过程中缺乏数据,这影响了系统的整体运行效果。本文根据大学节能监控和管理平台的运作,分析了近年来积累的建筑电力消耗的数据。本文选择典型的计量分支数据,建立指数平滑模型,预测日常功耗,并与实际值相比分析预测结果,以验证预测模型的效果。同时,它还为其他大学的节能监督平台进行了数据预测。

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