Solar PV Hotspot Multi-source Intelligent Detection System
光伏电站热斑多源智能检测系统
Addressing pain points in solar PV power plant hotspot detection including low accuracy, high miss/false alarm rates in drone inspections, and imprecise operations data supervision, integrating multi-source information from drone infrared images, string IV curves, and meteorological data to achieve precise hotspot localization and intelligent diagnostic decision-making.
npx openclaw skills install industry-solar-pv-hotspot-multi-source-intelligent-detectionFeatures
- **无人机红外图像智能分析**：基于YOLO+Transformer混合架构对无人机红外图像进行实时推理，自动识别热斑、隐裂、二极管故障等缺陷，漏检率降低至5%以下
- **组串IV曲线异常诊断**：接入组串逆变器的IV曲线数据，基于时序分析和对比算法识别潜在热斑隐患，提前3-7天预警即将恶化的组件
- **气象-发电量关联分析**：融合辐照度、温度、风速等气象数据与实际发电量，建立热斑影响量化模型，智能评估热斑对发电量损失的影响程度
- **运维决策智能推荐**：综合热斑严重等级、位置分布、天气窗口期，生成最优清洗/维修计划，自动排期并推送工单至运维人员移动端
Use Cases
- **无人机巡检智能辅助**：运维人员完成无人机巡检后上传红外图像，系统自动标注热斑位置并生成检测报告，标注置信度和处理优先级
- **热斑影响评估与运维决策**：在分析大屏上查看某光伏电站的热斑分布热力图、累计发电损失估算，选择重点区域生成清洗维护工单
Installation
npx openclaw skills install industry-solar-pv-hotspot-multi-source-intelligent-detection
使用示例
`分析西北某100MW电站最近一次无人机巡检的红外图像，识别并定位所有热斑组件`
`查询近7天因热斑导致的发电量损失，生成运维优先级清单`
`对比组件#A-15-0234的当前IV曲线与标准曲线，诊断是否存在热斑隐患`