arXiv research paper on applying graph machine learning to photovoltaic power forecasting for grid edge intelligence. Technical case study combining graph neural networks with solar energy prediction for smart grid optimization.
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On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence
Graph neural networks improve solar power forecasting accuracy for real-time grid edge optimization — enabling smarter demand-response coordination for renewable-heavy grids.
Thursday, April 23, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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