Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China

Abstract

Increasing the popularity of distributed photovoltaic technology among Chinese residents is of great significance to achieve the dual carbon goal (emission peak and carbon neutrality). In this study, we collected 1424 questionnaire samples and used PLS-SEM for group modeling and comparative analysis of bungalow and building residents. The results show that living conditions, costs, risks of installation, maintenance, and economic efficiency are the five significant influencing factors for residents to decide whether to install a distributed residential photovoltaic equipment. Compared with building residents, bungalow residents tend to feel more concerned about the cost and risk of residential photovoltaic equipment during installation, maintenance, and use. On the other hand, bungalow residents show greater sensitivity to the corresponding photovoltaic promotion policies. By contrast, building residents pay more attention to the direct benefit created by the installation of residential photovoltaic equipment. Therefore, adopting the strategy from bungalow residents to building residents could help promote the distributed photovoltaic system progressively. As for the subsidy decline, more attention shall be paid to the progress of a gradual reduction of the subsidies. It is advisable to pay attention to integrating the upstream and downstream industry chains of the distributed photovoltaic systems, thus reducing the concern of residents about the difficulty in installing, maintaining, and protecting the distributed photovoltaic equipment. By clarifying the different impacts of promotion policies on the demand side, this study provides a practical reference for the further adjustment made to distributed photovoltaic promotion policies.

Public acceptance of residential photovoltaic installation: A case study in China

“…These findings align with previous research and have practical implications for the Chinese government's PV subsidy policies. For instance, Wang et al [ 24 ] and Wang et al [ 58 ] mentioned this phenomenon in their research [ 24 , 58 ], indicating that to further promote residential PV at the current stage, economic incentive policies, such as subsidies, still need to be prioritized. Li et al [ 75 ] believe that publicity and guidance can also improve residents' willingness to install.…”

“…Therefore, residential PV equipment cannot be installed independently (a decision must be made by the owners' meeting in accordance with Chinese law). Previous studies by Wang et al [ 58 ] and Wang et al [ 24 ] explained the complexity of building residents installing residential PV using the theory of psychological distance and the TAM model, respectively. They suggested that building residents might have a more distant perception of residential PV and face challenges owing to incomplete property rights.…”

“…Statistical yearbook data of Hebei, Shandong and Henan provinces indicate that their population structure and energy structure ratios [ [79] , [80] , [81] ] are similar to those in the national statistical yearbook of 2021 [ 78 ], Hebei, Shandong, and Henan accounted for 84.6 % of the country's residential PV projects subsidized by national finance in 2021 (40.2 %, 32.3 %, and 12.1 %, respectively) [ 58 , 69 ], so data from these provinces would be more representative ( Appendix S2 shows detailed population and energy structure). These provinces provided a typical sample for the analysis of purchase deciding factors and intention among different groups.…”

“…This study investigates the relationship between PR and PG and residents' willingness to install PV systems on residential buildings under different living conditions (bungalows and buildings). The intermediary variables are AT, SN, and PBC from the TPB model [ 45 ], the PR comes from the research of Stern [ 61 ] and Kim et al [ 39 ], and the PG comes from the study of Wang et al [ 58 ]. The integration of external and internal factors is intuitive and efficient, as shown in Fig.…”

“…The main variables are measured using a Likert 5-point scale, and the measurement scale and detailed questions are shown in Appendix S1 . The PR was referenced from Stern [ 61 ] and Kim et al [ 39 ], while the PG was referenced from Wang et al [ 58 ]. Soliman et al [ 68 ] used PA, SN, PBC, and II, referenced from Ajzen [ 45 ] and Wolske et al [ 48 ].…”