Smart Grid and Optimization-Based Scheduling of Power Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".
Deadline for manuscript submissions: 20 June 2024 | Viewed by 1478
Special Issue Editors
Interests: smart grid; time series analysis; cyber physical security; deep learning; optimization and demand response for smart grid
Interests: control theory; geometry; differential geometry; energy
Special Issues, Collections and Topics in MDPI journals
Interests: modern power systems and renewable energy; power protection systems; smart grid; load forecasting as well as control system and modelling of energy storage systems; applying emerging technologies such as machine learning and optimization methods for micro and smart grid
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Smart grid technology has emerged as a significant technological advancement in the power sector, one which enables efficient and reliable energy management. With the growing demand for renewable energy and distributed energy resources, traditional power systems have become more complex and the need for advanced power scheduling algorithms has become inevitable. Optimization-based scheduling techniques have proven effective in achieving energy efficiency, reducing costs, and ensuring grid stability. In this context, integrating smart grids and optimization-based scheduling can significantly improve the performance and resilience of power systems.
Integrating smart grids and optimization-based scheduling requires the development of advanced algorithms that can effectively manage the complex nature of the power grid. Researchers have proposed several methods to achieve the efficient scheduling of power systems, including linear programming, dynamic programming, and the use of metaheuristic algorithms. These techniques aim to minimize energy costs, reduce greenhouse gas emissions, and improve the grids’ overall performance. Moreover, integrating smart grid technologies, such as advanced metering infrastructure, demand response, and energy storage systems, can further enhance the effectiveness of these scheduling algorithms.
Despite the potential benefits of smart grids and optimization-based scheduling, several challenges must be addressed to ensure their successful implementation. These challenges include achieving data security, establishing communication protocols, and integrating renewable energy sources. Additionally, the development of standardized protocols and regulatory frameworks is crucial to ensure the compatibility and interoperability of smart grid technologies. Therefore, further research is needed to address these challenges and develop advanced optimization-based scheduling techniques with which to manage the evolving power grid efficiently.
Overall, the integration of smart grids and optimization-based scheduling constitutes an emerging field which has significant potential to revolutionize the power sector. The development of advanced algorithms and the integration of smart grid technologies can lead to the development of efficient, reliable, and sustainable power systems. Therefore, further research in this area is critical to realize the full potential of smart grids and optimization-based scheduling in the power sector.
Dr. Ayush Sinha
Prof. Dr. William Holderbaum
Dr. Feras Alasali
Guest Editors
Manuscript Submission Information
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Keywords
- smart grids
- time series
- cyber physical security
- deep learning
- optimization
- demand response
