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AI in Energy: Overcoming Unforeseen Obstacles

Mir Sayed Shah Danish

2023AI43 citationsDOIOpen Access PDF

Abstract

Besides many sectors, artificial intelligence (AI) will drive energy sector transformation, offering new approaches to optimize energy systems’ operation and reliability, ensuring techno-economic advantages. However, integrating AI into the energy sector is associated with unforeseen obstacles that might change optimistic approaches to dealing with AI integration. From a multidimensional perspective, these challenges are identified, categorized based on common dependency attributes, and finally, evaluated to align with the viable recommendations. A multidisciplinary approach is employed through the exhaustive literature to assess the main challenges facing the integration of AI into the energy sector. This study also provides insights and recommendations on overcoming these obstacles and highlights the potential benefits of successful integration. The findings suggest the need for a coordinated approach to overcome unforeseen obstacles and can serve as a valuable resource for policymakers, energy practitioners, and researchers looking to unlock the potential of AI in the energy sector.

Topics & Concepts

Energy sectorMultidisciplinary approachRisk analysis (engineering)Dependency (UML)Energy (signal processing)Computer scienceResource (disambiguation)Perspective (graphical)Reliability (semiconductor)Efficient energy useManagement scienceProcess managementBusinessArtificial intelligenceEngineeringEnvironmental economicsPolitical scienceEconomicsPower (physics)Quantum mechanicsMathematicsLawStatisticsElectrical engineeringComputer networkPhysicsEnergy Efficiency and ManagementEnergy, Environment, Economic GrowthMarket Dynamics and Volatility