UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Enhancing energy efficiency in air source heat pump central heating systems: a method and case study on optimized sequencing control with improved heat supply and demand predictions

Tian, Yanan; Chen, Xu; Sun, Yuying; Wei, Wenzhe; Wang, Wei; Wei, Shen; (2025) Enhancing energy efficiency in air source heat pump central heating systems: a method and case study on optimized sequencing control with improved heat supply and demand predictions. Applied Thermal Engineering , 280 (3) , Article 128292. 10.1016/j.applthermaleng.2025.128292.

[thumbnail of Wei_Revised manuscript-unmarked.pdf] Text
Wei_Revised manuscript-unmarked.pdf
Access restricted to UCL open access staff until 16 September 2026.

Download (1MB)

Abstract

With the development of clean heating, air source heat pump central heating (ASHP-CH) systems with multiple fixed-frequency units are widely adopted. However, traditional sequencing control leads to frequent start-stop cycles of ASHPs and reduced efficiency. Step-change variations and noise in operational data hinder accurate prediction of heating load and ASHPs’ performance, challenging precise unit number adjustment. To address these challenges, this study developed a model-based sequencing framework that leverages improved heat supply and demand predictions. First, wavelet coherence analysis is employed to identify the temporal scales where heating load more strongly correlates with meteorological factors, thereby enabling accurate load forecasting based on step-changed data. Second, a dual-stage clustering method based on minimizing information entropy is utilized to enhance the robustness of the ASHP performance prediction model. Finally, a novel sequencing control strategy is proposed based on heat supply–demand matching. The proposed strategy was implemented in an ASHP-CH system in a residential community in Xinzhou City in order to verify its effectiveness. Test results show that the improved heating load and ASHP models markedly raise prediction accuracy, with R<sup>2</sup> value increased by 0.49 and 0.16, respectively. Moreover, the proposed strategy reduces ASHP unit start-stop cycles by 86%, decreases the heating system's electricity consumption by 13.00%, and increases the coefficient of performance of the ASHP units and the heating system by 11.23% and 10.16%, respectively. These findings verify that accurate predictions of heat supply and demand can enable efficient, stable operation of ASHP-CH systems, providing a practical solution for optimal sequencing control.

Type: Article
Title: Enhancing energy efficiency in air source heat pump central heating systems: a method and case study on optimized sequencing control with improved heat supply and demand predictions
DOI: 10.1016/j.applthermaleng.2025.128292
Publisher version: https://doi.org/10.1016/j.applthermaleng.2025.1282...
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Air source heat pump, Heating system, Sequencing control strategy, Wavelet coherence analysis, Dual-stage clustering, Model predictive control
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10214322
Downloads since deposit
1Download
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item