Evaluation Of Carbon Saving And Emission Reduction In Qinghai Tibet Plateau Based On Solar Power Generation Potential

Solar energy is a kind of renewable energy with great development potential.With its high-quality resource attributes such as low pollution,large reserves,and low cost,it has broad development prospects around the world.Therefore,countries around the world have increased their research investment in the solar energy field.With the help of the dual-carbon policy,China has actively issued a series of supporting policies in the field of photovoltaic power generation,and carried out key research and development in the Qinghai-Tibet Plateau,to change our country’s current energy structure dominated by fossil energy.Taking this opportunity as an opportunity,this paper selected the potential of solar photovoltaic power generation as the research object.Based on reading a large number of works of literature,and policy documents,and referring to previous studies,it analyzes various factors affecting the development and utilization of solar energy and combines a large number of collected and inverted data.Based on remote sensing data,the OWA（Ordered Weighted Averaging）algorithm was introduced to establish a corresponding index evaluation system to comprehensively evaluate the potential of photovoltaic power generation in the Qinghai-Tibet Plateau,and to study the suitability of centralized photovoltaic power plants in the Qinghai-Tibet Plateau.The U-NET network in deep learning technology was introduced to extract the roofs of urban buildings in the main urban areas of various cities in the Qinghai-Tibet Plateau and estimate the available rooftop solar energy area.According to the relevant policy documents in my country,combined with the suitable area of the centralized photovoltaic power station and the available roof area of the distributed photovoltaic power station,a quantitative analysis of the photovoltaic power generation potential in the Qinghai-Tibet Plateau was carried out.Combined with my country’s Energy Statistical Yearbook,this paper discusses the carbon saving and emission reduction benefits of photovoltaic power generation potential to replace thermal power generation and puts forward corresponding policy suggestions.After analyzing the research data,this paper draws the following conclusions:（1）The spatial heterogeneity of centralized photovoltaic power generation potential in the Qinghai Tibet Plateau is obvious.There are orders of magnitude differences in power generation potential in different regions.The cumulative proportion of power generation potential of prefecture-level cities ranking 1-2 in power generation potential has reached 86.12%.Qinghai Haixi Mongolian and Tibetan Autonomous Prefecture is the most suitable area for constructing photovoltaic power stations in the Qinghai Tibet Plateau.Its power generation potential is far higher than that of other prefecture-level cities.（2）The power generation potential of distributed photovoltaic power stations in various cities in the Qinghai-Tibet Plateau is step-like.The first echelon is two provincial capital cities,accounting for 62.36%of the total value of the Qinghai-Tibet Plateau;the second echelon is Shigatse,Nagqu,and other 10 cities;The three echelons are Qamdo,Haibei,and Guoluo.The power generation potential of distributed photovoltaic power stations in Xining is higher than that in Lhasa,while the power generation potential of non-capital cities in Tibet is higher than that in Qinghai.In the comparison of various prefecture-level cities,the potential of centralized photovoltaic power generation often has a certain negative correlation with the potential of distributed photovoltaic power generation.（3）The annual photovoltaic power generation potential of the Qinghai-Tibet Plateau reaches 3.46×10¹³ kW·h,and its spatial concentration is high,with 90.15%located in Guoluo,Yushu,and Haixi in Qinghai Province.Photovoltaic power generation potential can replace all the current thermal power generation in the Qinghai-Tibet Plateau and can reduce the carbon emissions of thermal power by 1.23×10¹² kg.