Data Analytics for Power System Operations
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: 15 March 2025 | Viewed by 162
Special Issue Editors
Interests: power system operation and optimization; energy market models; energy storage; renewable resources and machine learning
Interests: lighting applications; power quality problems in power systems; grid integration of (marine) renewable energy; design; performance analysis; and cost benefit analysis of (marine) renewable energy systems; energy management; energy systems; smart grids
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The power system industry is rapidly evolving, driven by the integration of renewable energy sources, the deployment of smart grid technologies, and the increasing complexity of power system operations. Data analytics plays a crucial role in addressing these challenges, offering innovative solutions for monitoring, control, optimization, and decision-making processes in power systems.
This Special Issue aims to provide a comprehensive platform for researchers, engineers, and practitioners to share their latest findings, methodologies, and applications of data analytics in power system operation. We invite high-quality original research papers, review articles, and case studies that explore the use of data analytics in enhancing the efficiency, reliability, and sustainability of power systems.
Topics of interest include, but are not limited to, the following:
- Big data analytics: techniques and tools for handling and processing large-scale power system data;
- Machine learning and artificial intelligence: applications of machine learning and AI in power system forecasting, fault detection, and system optimization;
- Advanced metering infrastructure (AMI): data analytics for AMI and its impact on power system operation;
- Renewable energy integration: data-driven approaches for integrating renewable energy sources into the grid;
- Demand response and energy management: analytics for demand response programs and energy management systems;
- Grid resilience and reliability: data analytics for enhancing the resilience and reliability of power systems;
- Cyber-physical systems: data analytics for securing and optimizing cyber-physical power systems;
- Predictive maintenance: data-driven predictive maintenance strategies for power system assets;
- Energy storage systems: data analytics for the operation and management of energy storage systems;
- Market analysis and optimization: data-driven approaches for power market analysis and optimization.
Technical Program Committee Member:
Dr. Amish Bhatt Grid Operations at Hydro One Inc
Dr. Amr Mohamed
Dr. Ahmed F. Zobaa
Guest Editors
Manuscript Submission Information
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Keywords
- data analytics
- data-driven
- machine learning
- artificial intelligence
- advanced metering infrastructure
- forecasting
- market
- predictive maintenance
- renewable energy sources
- smart grids
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