Computational Intelligence for Optimal Design and Operation of Microgrids
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 June 2024 | Viewed by 168
Special Issue Editors
Interests: evolutionary computation techniques; neural networks; optimization of EM devices; reflectarray antennas; electrical microgrid
Special Issues, Collections and Topics in MDPI journals
Interests: photovoltaics; PV power forecasting; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: photovoltaic system; grid; power sharing; inverters; forecasting; nowcasting; machine learning; degradation; battery management systems; polymer solar cells; organic photovoltaics; electric vehicle; vehicle-to-grid; microgrid; energy systems; maximum power point trackers; electric power plant loads; electricity price; power markets; heterogeneous networks; base stations; energy efficiency; life cycle assessment; wind power; regenerative braking; bicycles; motorcycles; car sharing; autonomous vehicles
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
A microgrid can be defined as a portion of an electric grid which operates in different layouts and conditions, and it includes distributed generation renewable power sources (mainly photovoltaic and wind), electrical loads, including electric vehicles, and batteries. In order for it to operate safely and uninterrupted, the microgrid should be smart, and for an optimized operation, it is important to forecast possible scenarios and predict faults for maintenance, which also involves a wider use of energy storage systems.
Computational Intelligence can be an effective tool for managing the biggest challenges for smart grids, microgrids, and renewable energy applications. In fact, they provide a wide range of flexible and effective tools, such as Artificial Neural Networks, Deep Learning, Fuzzy Logic Systems, Evolutionary Programming, and Evolutionary Optimization.
These methodologies and their hybridizations can be applied for the optimal design and the effective operations of microgrids. They can be employed in different areas and for different applications, like the estimation of exploitable energy, the sizing and management optimization of the microgrid, the application of predictive maintenance, and many other applications.
This Special Issue will focus on new ideas, and it will explore the inherent challenges in developing future microgrids, investigating novel designs and effective operations. It will explore enabling technologies and share relevant experiences regarding Computational Intelligence and Machine Learning methods.
Potential topics include, but are not limited to:
- Computational Intelligence for modeling and control of integrated renewable power generation systems.
- Estimation by means of Machine Learning and neuro-fuzzy techniques of the exploitable energy from different power sources in the following time horizons: very short (30 s to 1 min), short (1 min to 15 min), and mid-term (1 day ahead).
- Load management and optimization, in smart grid, microgrid, or smart buildings.
- Sizing and optimization of the components in the microgrid.
- Predictive Maintenance for the evaluation of reliability of the components.
- Estimation of the remaining useful life and reliability analysis of the components in the power system (batteries, inverters, etc.).
- Innovative Maximum PowerPoint Tracking algorithm by means of Heuristic Techniques.
- Application of GIS for the estimation of renewable energy capacity or for the analysis of the microgrid location and distribution.
Dr. Alessandro Niccolai
Dr. Emanuele Ogliari
Prof. Dr. Sonia Leva
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- microgrids
- computational intelligence
- machine learning
- evolutionary and swarm optimization
- optimal design
