Economic Value Creation of Artificial Intelligence in Supporting Variable Renewable Energy Integration: A Systematic Review of Power System Applications

This systematic review aims to elucidate the economic value creation of Artificial Intelligence (AI) in supporting the integration of Variable Renewable Energy (VRE) sources into power systems. Addressing the economic dispatch challenges associated with integrated power system has become paramount due to the increasing penetration of VRE. This paper reviews the role of AI in mitigating costs related to balancing, profile, and grid with a focus on its applications for generation and demand forecasting, market design, demand response, storage solutions, power quality enhancement, and predictive maintenance. By analyzing the use cases across various renewable energy resources (RERs), including wind, solar, geothermal, hydro, ocean, bioenergy, hydrogen, and hybrid systems, this study highlights AI’s potential to enhance economic efficiency and operational reliability. This review spans the literature from 2014 to 2024, offering insights into the advancements and limitations of AI-driven approaches in the renewable energy sector. The findings underscore AI’s critical role in optimizing VRE integration, ultimately facilitating a more resilient and economically sustainable energy landscape.