S. Srinivasa senthil, K. Vijayakumar^*

Energy Engineering, Vol.122, No.12, pp. 5149-5173, 2025, DOI:10.32604/ee.2025.070889 - 27 November 2025

Abstract Heating, ventilation, and air conditioning (HVAC) systems contribute substantially to global energy consumption, while rejecting significant amounts of low-grade heat into the environment. This paper presents a non-intrusive spiral-coil heat exchanger designed to recover waste heat from the outdoor condenser of a split-type air conditioner. The system operates externally without altering the existing HVAC configuration, thereby rendering it suitable for retrofitting. Water was circulated as the working fluid at flow rates of 0.028–0.052 kg/s to assess thermal performance. Performance indicators, including the outlet water temperature, heat transfer rate, convective coefficient, and efficiency, were systematically evaluated.… More >

Alya Penta Agharid¹, Indra Permana², Linlan Chang¹, Yi-Han Luo², Fujen Wang^2,*

Energy Engineering, Vol.122, No.9, pp. 3839-3866, 2025, DOI:10.32604/ee.2025.068586 - 26 August 2025

Abstract Air conditioning (AC) is essential for maintaining indoor comfort during Taiwan’s hot and humid summers but significantly contributes to increased energy consumption. This study evaluates the effects of AC duty-cycling strategies on energy performance, thermal comfort, and operational costs in office environments. Duty-cycling was implemented using a building energy management system (BEMS), which remotely controlled the ON/OFF cycles of AC units. Five duty-cycling modes were tested, with some modes incorporating air circulation during OFF periods. Field measurements of energy consumption, temperature, humidity, and air velocity were conducted and integrated with thermal comfort analysis tools to… More >

Lifan Zhao^1,2, Zetian Huang^1,2, Qiming Fu^1,2,3,*, Nengwei Fang⁴, Bin Xing⁴, Jianping Chen^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2741-2758, 2023, DOI:10.32604/cmes.2023.025500 - 09 March 2023

Abstract Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed More >