摘要
结合市辖区层面光伏发展情况以及城市中不同用地的特点,利用卫星图片识别长沙市各地区适合装设分布式光伏的建筑区域。基于太阳高度角和方位角,通过山体阴影分析屋顶上的建筑阴影,计算地区屋面光伏可承载容量。对市场侧、制造商及电网部门的分布式光伏规划进行研究。通过识别结果可为光伏建设方及电网提供明确地域列表及可用面积,以及可实现基于实际建设项目的可新增光分布式光伏装机容量的预测,以期为分布式光伏电站用地不足问题提供新的解决思路。
Combined with the development of photovoltaic technology at the municipal level and the characteristics of different land uses in the city.Satellite images are used to identify building areas suitable for installing distributed photovoltaic technology in various regions of Changsha City.Based on the sun's altitude and azimuth angles,the shadow of buildings on the roof is analyzed through mountain shadows to calculate the rooftop photovoltaic carrying capacity of the area.Conduct research on distributed photovoltaic planning for market side,manufacturers,and power grid departments.The experiment provides a clear geographical list and available area for the photovoltaic construction party and the power grid through identification results,as well as a prediction of the newly added distributed photovoltaic installed capacity based on actual construction projects,providing new solutions to the problem of insufficient land for distributed photovoltaic power stations.
作者
彭曙蓉
何洁妮
刘韬文
李彬
苏盛
壮婕
Peng Shurong;He Jieni;Liu Taowen;Li Bin;Su Sheng;Zhuang Jie(School of Electrical and Information Engineering,Changsha University of Science and Technology,Changsha 410114,China;State Grid Yiyang Power Supply Company,Yiyang 413000,China;State Grid Hunan Electric Power Company Dispatching and Control Center,Changsha 410004,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2024年第5期517-526,共10页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51777015)。
关键词
可再生能源
分布式发电
深度学习
语义分割
卫星图像
renewable energy
distributed power generation
deep learning
semantic segmentation
satellite imagery
