The study of the dynamic load forecasting model about air-conditioning system based on the terminal user load

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

14 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)263-268
Journal / PublicationEnergy and Buildings
Volume94
Publication statusPublished - 1 May 2015

Abstract

The energy-saving optimization control strategies of central air-conditioning system widely used now is according to the operation parameters of the cold source side to adjust the load supply. But the operation parameter describes the centralized and hysteresis effect about the central air conditioning system in current load. The effects can't well reflect the actual change about the user load and ensure the comfort of all users. It will be better if directly regulate the cold source of central air conditioning load according to the needs of the terminal users. Based on this idea, the study calculates the load of the terminal air-conditioning equipment according to its operating parameters, and then the dynamic load forecasting methods is used to establish the forecasting model that can forecast in real-time the load demand in the next time. The load forecasting methods do not need to analyze the factors that directly affect indoor load changes and to establish the load changes physical model. It use "the degree of load changes" to describe the load variation influence so to avoid the randomness and uncertainty about the change of the air-conditioning system load. The experimental results show that the forecasting model has well prediction effect. With the support of network control technology, all the terminal user load demand can be got, so the total load about the central air-conditioning based the terminal user forecasting load can be got. The better energy-saving optimization control strategies of central air-conditioning system will be get to use the forecasting load as the basis of the energy saving control for the central air conditioning cold source system.

Research Area(s)

  • Central air-conditioning, Energy-saving, Load forecasting, Network control