建筑与文化Issue(3)：244-247,4.DOI:10.19875/j.cnki.jzywh.2025.03.074
基于改进Mask R-CNN的建筑屋面光伏利用潜力评估研究——以长春市工业厂房为例
Study on the Evaluation of Photovoltaic Utilization Potential of Building Roofs Based on an Improved Mask R-CNN Algorithm:A Case Study of Industrial Plants in Changchun City
摘要
Abstract
In recent years,China's energy demand has grown rapidly along with its economy.Utilizing solar energy resources on building roofs is an important way to achieve China's carbon peak and carbon neutrality goals.This study proposes an improved Mask R-CNN deep learning algorithm to enhance the model's feature extraction capability by upgrading the FPN network in the original model to a PAN network,thereby improving the efficiency of photovoltaic potential assessment.The study focuses on industrial plants in the central urban area of Changchun City,evaluating the PV potential of their roofs.It is calculated that the total roof area of industrial plants in the central urban area of Changchun City is 82.48×106 m2,and the PV potential is 144.4375×108 kWh/year,providing a basis for the development planning of rooftop PV systems for industrial plants in Changchun City.关键词
Mask R-CNN/建筑屋面/光伏利用潜力/长春市工业厂房Key words
Mask R-CNN/building roof/photovoltaic utilization potential/Changchun industrial plant引用本文复制引用
周春艳,路少石..基于改进Mask R-CNN的建筑屋面光伏利用潜力评估研究——以长春市工业厂房为例[J].建筑与文化,2025,(3):244-247,4.基金项目
吉林省教育厅科技项目(项目编号:JJKH20240367KJ) （项目编号:JJKH20240367KJ）
吉林省教育科学规划项目(项目编号:GH23596) （项目编号:GH23596）
