Solar PV Power Prediction and Operation Maintenance Optimization Decision System
光伏电站功率预测与运维优化决策系统
A skill for power prediction and operation maintenance optimization for solar PV plants and distributed PV stations. Based on meteorological forecast data (irradiance, temperature, wind speed), PV module characteristic parameters and historical generation data, it uses multi-model integration methods (physical model + statistical model + AI model) to achieve short-term and ultra-short-term power forecasting, providing reliable data support for grid dispatching, while combining equipment fault diagnosis and soiling analysis to optimize maintenance priorities and cleaning strategies.
npx openclaw skills install industry-solar-pv-power-prediction-optimizationFeatures
- **短期功率精准预测**: 基于数值天气预报（NWP）和光伏组件电气特性模型，提前24-72小时预测电站总出力，预测精度（RMSE）优于行业标准15%以上，为电网日前调度计划提供可靠依据
- **超短期功率滚动预测**: 结合卫星云图和地面辐射仪数据，每15分钟滚动更新未来4小时出力预测，捕捉云层快速移动对发电的影响，支持AGC自动功率控制和实时调度
- **设备健康状态实时诊断**: 基于组串级逆变器输出电流电压数据，运用机器学习算法识别光伏组件衰减、热斑、连接器烧毁、逆变器效率下降等异常，支持组件级定位和故障告警
- **灰尘累积智能监测与清洗决策**: 通过辐照度损失分析、环境传感器数据和AI图像识别，综合评估组件表面灰尘污染程度，生成区域化的最优清洗时机和范围建议，避免过度清洗或清洗不足
- **运维成本效益优化分析**: 综合发电量损失成本、运维人力成本、清洗水耗成本和设备更换成本，构建运维经济性评估模型，生成季度/年度的最优运维策略和预算计划
Use Cases
Installation
npx openclaw skills install industry-solar-pv-power-prediction-optimization
Usage Examples
`查询明天的96点功率预测曲线和置信区间`
`诊断当前所有组串的健康状态，输出异常清单`
`生成未来一周的最优组件清洗计划`
`分析本月功率预测偏差原因和改进建议`