Sustainable Energy Policies Formulation Through the Synergy of Backcasting and AI Approaches

This study focuses on the implementation of backcasting and artificial intelligence (AI) in energy policy development, emphasizing sustainable and equitable solutions for future challenges. The research introduces the backcasting methodology, a reverse-engineered approach focused on achieving desired future outcomes by analyzing the necessary steps from a future standpoint. This chapter provides a detailed implementation roadmap through a case study approach, demonstrating the practical application of backcasting in aligning energy policies with the Sustainable Development Goals (SDGs). Additionally, it introduces the ASHES framework (Assess, Strategize, Harmonize, Execute, and Sustain), a multidimensional tool integrating AI to enhance energy policy development. The framework’s application is explored through a hypothetical scenario, showcasing its efficacy in addressing renewable energy adoption and emission reductions while considering socioeconomic and ethical dimensions. This chapter also discusses the energy and carbon supply chain, highlighting the role of various sectors and technologies in managing emissions and leveraging AI. A systematic analysis of these components is presented, using a value-chain representation to illustrate the interconnected nature of these elements. This study culminates in a discussion on the challenges, opportunities, and future directions for integrating AI in energy policy, emphasizing the need for a multidisciplinary approach and stakeholder collaboration.