In AI, Technical Paper
Can advanced forecasting predict solar irradiance & wind speed with 98% accuracy?
Solar PV plants face some pertinent challenges today. Unpredictable and fluctuating future solar irradiance and wind speed are one of them. The present solar and wind forecasting services are unable to provide accurate predictions. Thus, in the absence of standard forecasting projections, renewable energy developers are not able to plan the future production, operations and maintenance of clean energy assets in a better way. Furthermore, it adversely impacts the investability and credibility of the existing and upcoming renewable energy projects, reducing their overall share in the clean energy market. As a result, renewable energy utilities have to bear the burden of hefty penalties for not being able to meet their energy commitments.
In a nutshell
- 🌎 We consider factors like the inter- and intra-day variability of the renewable energy resources, human or anthropogenic and local environmental factors, global climatic events, and climate change.
- 📡 We blend climate science, satellite imagery/data, global meteorological databases, AI, ML, and Deep-Learning to take the predictions to the next level of forecasting accuracy band.
- 💻 We developed an AI-based framework to automatically select the best models, factors, and their combinations to optimize the overall accuracy of the predictions. The results were more than 98% accurate.
Who is this for?
- 🔧 Asset Managers and O&M Professionals
- 💰 Solar Investors and Stakeholders
- 💫 Industry Leaders and CXOs
