PMV-based dynamic optimization of energy consumption for a residential task/ambient air conditioning system in different climate zones. (November 2019)

• Record Type: Journal Article
• Authors: Mao, Ning; Hao, Jingyu; He, Tianbiao; Song, Mengjie; Xu, Yingjie; Deng, Shiming
• Is Part Of: Renewable energy. Volume 142(2019)
• Page Start: 41
• Page End: 54
• Publication Date: 2019-11
• Subjects: Bedroom TAC system -- Energy saving -- PMV-based strategy -- Sleeping thermal comfort; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2019.04.099
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Considering the effects of climate zones on building energy, a numerical study was conducted to investigate the energy consumption of a bedroom task/ambient air conditioning (TAC) in different climate zones. In this study, a PMV-based operating strategy of TAC was proposed to dynamically control energy consumption during night. According to this operating objective, the TAC was operated at two conventional operating modes: variable supply air temperature mode (VAT) and variable supply air flow rate mode (VAF). It's found that compared to VAF mode, VAT mode help reduce energy consumption by no less than 10% in Beijing, 19% in Shanghai and 18% in Guangzhou. To further reduce operating power, the variable air flow rate and air temperature mode based on lowest energy consumption (VFT-LowE) was adopted to optimize the operating of TAC, and the results show that compared to VAT, VFT-LowE mode can save energy by up to 6.5% in Guangzhou. Moreover, the highest energy saving potential was also evaluated showing a highest energy saving per night of 403 kJ in Beijing, and around 1100 kJ in Shanghai and Guangzhou. It's also indicated that the optimized operating mode has the largest energy saving potential in climate zones with higher air temperature. Highlights: A CFD study was conducted on TAC system applied in different climate zones. RSM method was used to predict energy consumption of TAC system. The TAC was operated under PMV-based strategy with two modes: VAT and VAF. Compared to VAF mode, VAT mode helped reduce energy consumption. The TAC was optimized by VFT-LowE mode which had the lowest energy consumption.