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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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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1721561651727040512 |