Research progress on PVACs and their application in buildings

doi:10.3969/j.issn.2097-0706.2026.04.001

Abstract

Abstract:

Photovoltaic-driven air conditioning （PVAC） systems offer a new approach to reducing building energy consumption and advancing carbon neutrality by integrating renewable energy with building thermal management capabilities. The technical principles and classification characteristics of PVAC systems are systematically reviewed， and their driving mechanisms are categorized into three main types： AC-driven， DC-direct-driven， and hybrid-driven. The research progress on PVAC in terms of energy transfer optimization， dynamic control strategies， and multi-parameter collaborative design is presented. It is demonstrated that the optimized PVAC systems can achieve efficient matching of photovoltaic power generation and refrigeration demand in high-temperature regions in summer， with energy consumption coverage of air conditioning increasing to 29.5%. Furthermore， the system scheme integrating phase change materials and variable-speed compressors can significantly increase the real-time zero energy probability. The integration of PVAC systems with buildings （i.e.， building-integrated photovoltaics） can not only enhance building performance but also improve the energy utilization efficiency of PVAC systems. However， there is still a lack of a unified evaluation indicator system for building-integrated photovoltaic systems. Future research is expected to provide new insights into improving PVAC system performance and promoting their large-scale application in buildings.

Key words: photovoltaic-driven air conditioning, building energy efficiency, parameter characteristics and evaluation indicator, control strategy, building-integrated photovoltaics

CLC Number:

TK01：TU18

CAI Yang, ZHENG Shanle, HUANG Yingxi, LIU Ziquan, AN Rongbang. Research progress on PVACs and their application in buildings[J]. Integrated Intelligent Energy, 2026, 48(4): 1-11.

Figures/Tables 6

Fig.1

Table 1

Fig.2

Fig.3

Table 2

Research results of typical PVAC system parameters

分类	参数	主要结论	分析方法	评价指标	参考文献
光伏参数	光伏容量	当P_PV（t）/L（t）=1时，性能最佳	数值分析	SCR，SSR，COP	[13]
	工作温度	温度升高会导致电荷载流子的迁移率降低，进而降低电池效率	数值分析	光伏电池温度	[38]
		工作温度每升高1 ℃，光电转换效率会降低0.08%~0.10%，输出电功率下降0.45%	试验测试	光电转换效率、输出电功率	[37]
		工作温度升高，光伏性能会降低	综述总结	光电转换效率、温度系数	[44]
	光伏材料	第一代为硅电池，第二代为薄膜电池，第三代为高效电池	综述总结	光电转换效率	[43]
	光伏倾角	在非理想位置下存在能量损失	数值分析	能量损失百分比	[47]
	MPPT类型	分为HC，INC，P&O和FLC，其中FLC表现最佳	数值模拟	动态响应性能、稳态性能	[46]
空调参数	压缩机类型	变速压缩系统在制冷和制热模式下分别实现50%和16%的能效提升	试验测试	熵效率、单位投资成本	[45]
空调参数	逆变器效率	需低温运行，受光伏输入功率影响较大，在特定辐照下效率可达最高	数值分析	辐照度分布、光伏组件技术	[48]
环境参数	辐照度	太阳辐照度增加，光伏发电效率增加	试验测试	光电转换效率、SSR	[15]
	季节	光伏系统在冬季的输出电功率相比夏季有所降低	数值模拟	输出电功率、光电转换效率	[49]
	风	风载荷使组件表面压力非均匀分布，降低光伏系统性能	试验测试	表面均压	[50]
	局部遮挡	局部遮挡会显著降低光伏系统的功率输出和效率	综述总结	能量获取效率	[51]
	空气污染	中国西部城市，气溶胶污染在2014—2018年年均减少4.8%~9.0%的光伏发电量	试验测试	输出电功率、收益	[52]
		空气污染显著降低光伏发电量	数值分析	输出电功率、收益	[53]
		污染物将减小透射率，降低光伏发电效率	综述总结	输出电效率	[54]

Table 2

Table 3

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模式	说明
仅光伏供电	当光伏发电量恰好与空调系统能耗相等时，将光伏系统产生的电量提供给空调系统使用
光伏发电盈余	当光伏发电量高于空调系统能耗时，光伏系统发出的电量除向空调系统供电外，其余全部并入公共电网
公共电网补充	在阴雨天或光伏系统发生故障时，若光伏发电不能满足空调系统的能耗需求，光伏系统与公共电网同时为空调系统供电