Global Energy Interconnection-China
Scope & Guideline
Fostering Collaborative Insights in Renewable Energy
Introduction
Aims and Scopes
- Integrated Energy Systems:
The journal emphasizes research on integrated energy systems that combine various energy sources, including renewables such as wind, solar, and hydrogen, to improve efficiency and sustainability. - Smart Grid and Cyber-Physical Systems:
It covers advancements in smart grid technologies and cyber-physical systems, focusing on enhancing the reliability, security, and efficiency of energy distribution and consumption. - Energy Storage and Management:
Research on energy storage solutions and management strategies is a core focus, addressing the challenges of fluctuating renewable energy supply and ensuring grid stability. - Carbon Emissions and Sustainability:
The journal explores methodologies for evaluating and reducing carbon emissions in energy systems, contributing to global sustainability goals. - Data-Driven Approaches and AI:
There is a strong emphasis on data-driven methodologies, including machine learning and AI, for optimizing energy system operations and predictive maintenance. - Policy and Economic Analysis:
The journal also engages in the policy and economic aspects of energy interconnection and sustainability, providing insights into market dynamics and regulatory frameworks.
Trending and Emerging
- Decentralized Energy Systems:
There is a growing emphasis on decentralized energy production and management systems, including microgrids and peer-to-peer energy trading, which enhance local energy resilience. - Advanced Energy Storage Technologies:
Research on advanced energy storage technologies, such as battery systems and hydrogen storage, is gaining traction as solutions to support renewable energy integration. - Cybersecurity in Energy Systems:
With the increasing digitization of energy systems, cybersecurity has become a critical focus, addressing vulnerabilities in smart grid infrastructures. - Integration of AI in Energy Management:
The application of artificial intelligence and machine learning for optimizing energy management, predictive maintenance, and operational efficiency is emerging as a significant theme. - Multi-Energy Coupling and Optimization:
Research on multi-energy coupling, where different energy carriers (electricity, heat, hydrogen) are integrated for optimized performance, is on the rise. - Climate Change Mitigation Strategies:
The journal is increasingly focusing on strategies for climate change mitigation, including carbon trading and sustainable energy policies.
Declining or Waning
- Conventional Energy Systems:
Research focused on traditional energy generation methods, such as coal and natural gas, has decreased as the emphasis shifts towards renewable energy and sustainability. - Simple Energy Forecasting Models:
There is a waning interest in basic energy forecasting models, with researchers moving towards more complex, data-driven approaches that incorporate machine learning and AI. - Static Grid Management Techniques:
Static approaches to grid management are becoming less common, as dynamic and adaptive strategies gain importance in the context of smart grids and real-time data utilization. - Basic Energy Efficiency Measures:
The focus on basic energy efficiency measures is diminishing, with more attention being given to comprehensive integrated strategies that encompass multiple energy sources and technologies.
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