Cover -- Title Page -- Copyright -- Contents -- Preface -- List of Contributors -- Chapter 1: AI for Renewables: Addressing Operational, Engineering, and Socioeconomic Adoption Challenges -- 1.1 Introduction -- 1.2 Opportunities and Challenges -- 1.3 Current High-priority Areas -- 1.3.1 Explainability and Trust in AI for Renewables -- 1.3.2 Model Transferability and Generalization -- 1.3.3 Grounding AI Models to Domain-specific Operational and Engineering Knowledge -- 1.4 Nascent Areas in the AI and Renewables Domain -- 1.5 Conclusion -- Bibliography

Chapter 2: Techno-economic Analysis for Offshore Renewable Energy Technologies Incorporating a Holistic O&M Model -- 2.1 Challenge -- 2.2 Case Study -- 2.2.1 Before State-of-the-art -- 2.2.2 Methodology -- 2.2.3 Results -- 2.3 Discussion -- 2.4 Conclusion and Future Work -- Bibliography -- Chapter 3: Making the Most of Data in Offshore Wind Energy: From Population to Physics-informed Modeling -- 3.1 Introduction -- 3.2 Autoregressive Gaussian Processes -- 3.3 Population Modeling of Wind Farm Wake Effects -- 3.3.1 A Switching GP-SPARX Model -- 3.3.2 A Case Study of a Simulated Wind Farm

3.3.3 Results -- 3.3.4 Discussion -- 3.4 Physics-informed Machine Learning for Wave Loading Prediction -- 3.4.1 Monopile Wave Tank Experiment -- 3.4.2 Model Structure -- 3.4.3 Results -- 3.5 Conclusions -- Acknowledgments -- Bibliography -- Chapter 4: Leveraging the Power of Informal Networks in Renewables -- 4.1 Challenge -- 4.2 Case Study -- 4.2.1 Before SOA: What Was the State-of-the-art/Accepted Solution in the Past? -- 4.2.2 Influencing and Educating Informal Networks -- 4.2.3 Methodology -- 4.2.4 Enabling Continuous Improvement Through ML and AI -- 4.2.5 Next Steps -- 4.2.6 Results

4.2.7 After: What Is the Accepted Solution Now? -- 4.3 Discussion -- 4.4 Conclusion and Future Work -- 4.4.1 Challenges and Opportunities -- Acknowledgments -- Bibliography -- Chapter 5: Relevance of AI in Addressing Barriers to Rooftop Solar Photovoltaic Adoption in Building Projects in Nigeria -- 5.1 Introduction -- 5.2 Literature Review -- 5.2.1 Overview of Rooftop Solar Photovoltaic Systems -- 5.2.2 Reluctance to Adopt Sustainable Energy Solutions in Nigeria -- 5.2.3 Barriers to Rooftop Solar Photovoltaic Adoption in Building Projects

5.2.4 Artificial Intelligence Solutions to Overcome Barriers to Rooftop Solar Photovoltaic Adoption -- 5.3 Research Methods -- 5.4 Results and Findings -- 5.4.1 Background of the Respondents -- 5.4.2 Background Information of the Respondents -- 5.4.3 Barriers to the Adoption of Rooftop Solar Photovoltaics and the Preferred AI-Solution -- 5.4.4 Mean Score (MIS) Analysis -- 5.4.5 Standard Deviation (S.D.) Analysis -- 5.4.6 Mann-Whitney Test Analysis -- 5.4.7 Exploratory Factor Analysis -- 5.4.8 Discussion and Implications of Findings -- 5.4.9 Mean Score -- 5.4.10 Exploratory Factor Analysis