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

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 tr...

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Main Authors: Wang Hongrui, Wei Ran
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_01006.pdf
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spelling doaj-b637f7ed18584e2c81219fea964fe1c32021-04-02T14:42:43ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011940100610.1051/e3sconf/202019401006e3sconf_icaeer2020_01006Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing ModelWang Hongrui0Wei Ran1Shandong UniversityHarbin Institute of TechnologyWith 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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_01006.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Wang Hongrui
Wei Ran
spellingShingle Wang Hongrui
Wei Ran
Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
E3S Web of Conferences
author_facet Wang Hongrui
Wei Ran
author_sort Wang Hongrui
title Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
title_short Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
title_full Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
title_fullStr Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
title_full_unstemmed Electricity Consumption Forecast of Energy Saving Monitoring and Management Platform based on Exponential Smoothing Model
title_sort electricity consumption forecast of energy saving monitoring and management platform based on exponential smoothing model
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description 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.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/54/e3sconf_icaeer2020_01006.pdf
work_keys_str_mv AT wanghongrui electricityconsumptionforecastofenergysavingmonitoringandmanagementplatformbasedonexponentialsmoothingmodel
AT weiran electricityconsumptionforecastofenergysavingmonitoringandmanagementplatformbasedonexponentialsmoothingmodel
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