The diffusion path of distributed photovoltaic power generation technology driven by individual behavior
| Autor: | Wang Xiuchun, He Xuedong, Sun Xiaoqian, Qin Meicui, Pan Ruiping, Yang Yuanyuan |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Energy Reports, Vol 11, Iss , Pp 651-658 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2352-4847 61023043 |
| DOI: | 10.1016/j.egyr.2023.12.009 |
| Popis: | The widespread adoption of distributed photovoltaic (PV) power generation technologies among electricity consumers is a crucial factor in enabling the power system's low-carbon transition. While extensive research has explored consumers' willingness to adopt this technology, prior studies have primarily focused on static psychological factors. This study, however, takes a heterogeneous behavioral perspective by examining the dynamic effects of individual behavioral interactions on technology diffusion. Utilizing behavior-driven simulation technology, we developed a diffusion model pertaining to photovoltaic power generation technology. The model enhances the explanatory capacity and predictive accuracy of subjects' behavioral choices by quantifying the effects of adoption scale and external economic interventions. Our simulation results indicate that residential environment constraints, resulting from individual behavioral differences, can influence the diffusion potential of technology. Furthermore, non-mandatory promotion methods are more effective in enhancing user adoption willingness. Interestingly, we found that free installation interventions tend to reduce the diffusion effect in later stages and should not be implemented in isolation. These insights can contribute to enhancing the diffusion of distributed PV power generation technology and furthering the development of low-carbon electricity. |
| Databáze: | Directory of Open Access Journals |
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