Smart Grids and Microgrids: From Simulations to Experimentation
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".
Deadline for manuscript submissions: 30 April 2024 | Viewed by 2297
Special Issue Editors
Interests: integration of renewable energy sources into the electric grid; smart grid and microgrid management; control and modeling; lightning modeling and its effect on transmission and distribution networks
Special Issues, Collections and Topics in MDPI journals
Interests: digitalization; renewable energy; power quality; smart grid; smart buildings; energy efficiency
Interests: renewable energy; wind energy; solar energy; smart grids; power system
Special Issue Information
Dear Colleagues,
The green energy transition is a major goal in the global energy sector. This is due to the need to reduce the emission of pollutants and greenhouse gases and to establish an alternative to expensive fossil fuels. In this context, smart grids and microgrids present promising solutions, mainly due to their ability to integrate Renewable Energy Sources (RESs) into the main grid and work in islanded configurations rather than the (today more frequently found) grid-connected one.
Despite the great flexibility of these systems, it is important not to forget that they require high-performing controls to guarantee continuity of service in any operating condition. The scientific literature is full of innovative and effective approaches; however, their validation is often carried out with simulations, which is obviously inferior to real experimentation.
In this framework, this Special Issue aims to collect the most up-to-date experiences evolving from classical simulations to real-life engineering applications.
Topics of interest for publication include, but are not limited to:
- Energy Management Systems (EMSs) for grid-connected microgrids;
- Tools for the participation of microgrids in national energy markets and energy communities;
- Digital twins of smart grids, microgrids, RES and, more generally, power distribution systems;
- Machine Learning (ML) tools for smart grids and microgrids;
- Real-time simulations for power production systems;
- Integration of real field measurements/device characterization into smart grid modeling and simulations;
- Hardware in the Loop (HIL), Power Hardware in the Loop (PHIL) and Rapid Control Prototyping (RCP) set-up.
Prof. Dr. Renato Procopio
Dr. Gabriela Sava
Dr. Minh Quan Duong
Guest Editors
Manuscript Submission Information
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Keywords
- hardware in the loop (HIL)
- power hardware in the loop (PHIL)
- rapid control prototyping (RCP)
- energy management systems (EMS)
- digital twin
- renewable energy sources (RESs)
- advanced control systems
- smart grid (SG)
- power quality (PQ)
- digitalization
- machine learning (ML)
