The Study of Economic and Environmental Benefits of Distributed Photovoltaic Power Generation Projects in Southern Zhejiang Province on Take the 8 Projects of Pingyang Aipu photovoltaic Power Generation Co., Ltd
Year: 2024
Type: article
Abstract: The objectives of this research were 1) to evaluate the economic benefits of distributed photovoltaic (PV) power generation projects, 2) to assess environmental benefits, and 3) to analyze factors influencing power generation capacity and initial investment. The sample consisted of eight distributed PV power plants operated by Pingyang Aipu Photovoltaic Power Generation Co., Ltd. in Pingyang County, Zhejiang Province, selected based on varying capacities and installation methods. Data collection tools included operational data from 2019, such as electricity generation, grid power, self-use electricity, investment amounts, and revenue details. Data analysis methods included descriptive statistics and calculations of payback periods, internal rates of return, and emission reduction effects. The research results were as follows: 1) The PV systems' average full-load power generation time in the first year was 954 hours, with an internal rate of return of 12.07% and a payback period of 7.73 years, indicating good economic benefits; 2) The energy payback period was 6.1 years, and the projects could save 19,767,413.75 kg of standard coal over 20 years, demonstrating significant environmental benefits; 3) Provincial subsidies accounted for 15.08% of total revenue, grid electricity tariffs for 12.56%, and enterprise self-use electricity for 72.36%. It is recommended to monitor national policy adjustments and their impact on the economic efficiency of photovoltaic projects, study the development of the photovoltaic industry under different international policies, and investigate the investment value of photovoltaic power stations in regions with varying solar radiation conditions.
Source: Journal of Roi Kaensarn Academi
Institution: Muban Chombueng Rajabhat University
Language: Thai
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7219263232
