New Research To Illuminate AI’s Role In Predicting Solar Power Generation

A new chapter exploring the cutting-edge application of Artificial Intelligence (AI) in predicting solar power generation is scheduled for release in August 2025.

The chapter, titled “Artificial Intelligence-Based Predictive Modeling for Accurate Solar Power Generation: A Comparison of SVR, ANN, and RFR Approaches,” will appear in the highly anticipated book, Computational Intelligence and Smart Technologies in Solar Thermal Systems, 1st Edition, published by CRC Press.

Authored by Hensard University Vice Chancellor, Prof. Dileep Kumar Mohanachandran, Uppin Chandrashekhar, Kalpana Venugopal, T Gopala, and N Achyutha Prasad, the 10-page chapter provides a comparative analysis of three prominent AI techniques – Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Random Forest Regression (RFR) – and their effectiveness in accurately forecasting solar power output.

As global demand for renewable energy sources continues to surge, the precise prediction of solar power generation is becoming increasingly crucial for grid stability, energy management, and the overall efficiency of solar energy systems. This research offers valuable insights into the strengths and limitations of different AI approaches, ultimately aiming to improve the reliability and predictability of solar energy integration.

Computational Intelligence and Smart Technologies in Solar Thermal Systems promises to be a comprehensive resource for researchers, engineers, and policymakers working in the field of solar energy. By highlighting the potential of computational intelligence, the book aims to accelerate the development and deployment of smart and efficient solar thermal systems.

The chapter abstract is currently available on the Taylor & Francis website: https://www.taylorfrancis.com/chapters/edit/10.1201/9781003634737-5/artificial-intelligence-based-predictive-modeling-accurate-solar-power-generation-dileep-kumar-mohanachandran-uppin-chandrashekhar-kalpana-venugopal-gopala-achyutha-prasad?context=ubx&refId=5c6a198b-f70e-48b8-b6a5-b0cd4aea7c56.

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