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The integration of renewable energy sources into power distribution systems frequently presents challenges for conventional energy management systems (EMS) due to the unpredictable and unstable characteristics of such energy sources. As a result, novel and cutting-edge solutions are required. This paper presents an intelligent web-based energy management system (iW-EMS) specifically designed to address the integration and optimization of distributed energy resources, as outlined in the proposed approach. The system incorporates a hybrid novel optimization approach that integrates simulated annealing and cone programming to effectively manage the distribution of energy resources and attain optimal outcomes from the proposed EMS. Additionally, it leverages generative AI services to create optimal scenarios based on historical data and real-time information, ensuring adaptability to the dynamic nature of renewable energy generation, providing a user-friendly and flexible web environment for scenario planning. The proposed framework facilitates seamless communication and collaboration among stakeholders involved in renewable energy integration, while also enabling the incorporation of real-world data sources such as weather forecasts and energy consumption patterns into the planning process.
Zhao et al. (Wed,) studied this question.