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Sustainability
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Advanced Control Strategies for Renewable Energy Systems and Sustainable Development
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Advanced Control Strategies for Renewable Energy Systems and Sustainable Development

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 1111

Special Issue Editors

Prof. Dr. Youssef Errami

E-Mail Website
Guest Editor
Faculty of Sciences, Chouaib Doukkali University, Eljadida, Morocco
Interests: renewable energy system control; power electronics systems; electric drives and electrical power engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Abdellatif Obbadi

E-Mail Website
Guest Editor
Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco
Interests: renewable energy system control; power electronics systems; electric drives and electrical power engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sahnoun Smail

E-Mail Website
Guest Editor
Laboratory Electronics, Instrumentation and Energy (LEIE), Physics Department, Faculty of Sciences, Chouaïb Doukkali University, El Jadida 24000, Morocco
Interests: renewable energy systems; non-destructive thermal testing

Special Issue Information

Dear Colleagues,

In recent years, with the growth of population and industrialization, there has been increasing attention on renewable energy sources, which are unlimited in nature and eco-friendly. In addition, these sources are expected to play a significant role in the future energy industry, becoming the main alternative to, and reaching the level of, conventional fossil resources.

This Special Issue aims to present recent advances related to the theory and control of all categories of renewable energy sources.

Topics of interest for publication include, but are not limited to, the following:

  • Renewable energy systems;
  • Back-to-back power converters;
  • New efficient renewable energy technologies;
  • Multi-level power converters for renewable energy sources;
  • Modelling, control and nonlinear control of renewable energy sources;
  • Fuzzy logic research;
  • AI learning approaches;
  • New control strategies for maximum power extraction;
  • Adaptive power electronic control algorithms for the efficient operation of integrated renewable energy sources;
  • Artificial intelligence control;
  • Optimal power flow control;
  • Practical implementation of control techniques;
  • Grid-forming power electronics systems and future grid code requirements.
  • Sustainable energy

Prof. Dr. Youssef Errami
Prof. Dr. Abdellatif Obbadi
Prof. Dr. Sahnoun Smail
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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • renewable energy conversion systems 
  • maximum power point tracking 
  • power electronic converter 
  • controllers of renewable energy systems 
  • control and optimization 
  • nonlinear controllers 
  • fault ride through 
  • artificial intelligence control 
  • fuzzy logic research 
  • deep learning 
  • sustainable energy

Published Papers (2 papers)

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Research

26 pages, 13435 KiB  
Article
Short-Term Prediction of Rural Photovoltaic Power Generation Based on Improved Dung Beetle Optimization Algorithm
by Jie Meng, Qing Yuan, Weiqi Zhang, Tianjiao Yan and Fanqiu Kong
Sustainability 2024, 16(13), 5467; https://doi.org/10.3390/su16135467 - 27 Jun 2024
Viewed by 352
Abstract
Addressing the challenges of randomness, volatility, and low prediction accuracy in rural low-carbon photovoltaic (PV) power generation, along with its unique characteristics, is crucial for the sustainable development of rural energy. This paper presents a forecasting model that combines variational mode decomposition (VMD) [...] Read more.
Addressing the challenges of randomness, volatility, and low prediction accuracy in rural low-carbon photovoltaic (PV) power generation, along with its unique characteristics, is crucial for the sustainable development of rural energy. This paper presents a forecasting model that combines variational mode decomposition (VMD) and an improved dung beetle optimization algorithm (IDBO) with the kernel extreme learning machine (KELM). Initially, a Gaussian mixture model (GMM) is used to categorize PV power data, separating analogous samples during different weather conditions. Afterwards, VMD is applied to stabilize the initial power sequence and extract numerous consistent subsequences. These subsequences are then employed to develop individual KELM prediction models, with their nuclear and regularization parameters optimized by IDBO. Finally, the predictions from the various subsequences are aggregated to produce the overall forecast. Empirical evidence via a case study indicates that the proposed VMD-IDBO-KELM model achieves commendable prediction accuracy across diverse weather conditions, surpassing existing models and affirming its efficacy and superiority. Compared with traditional VMD-DBO-KELM algorithms, the mean absolute percentage error of the VMD-IDBO-KELM model forecasting on sunny days, cloudy days and rainy days is reduced by 2.66%, 1.98% and 6.46%, respectively. Full article
(This article belongs to the Special Issue Advanced Control Strategies for Renewable Energy Systems and Sustainable Development)
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15 pages, 4003 KiB  
Article
Design and Performance Analysis of a Small-Scale Prototype Water Condensing System for Biomass Combustion Flue Gas Abatement
by Valentina Coccia, Ramoon Barros Lovate Temporim, Leandro Lunghi, Oleksandra Tryboi, Franco Cotana, Anna Magrini, Daniele Dondi, Dhanalakshmi Vadivel, Marco Cartesegna and Andrea Nicolini
Sustainability 2024, 16(12), 5164; https://doi.org/10.3390/su16125164 - 18 Jun 2024
Viewed by 538
Abstract
This article outlines the design and performance of a flue gas condensation system integrated with a biomass combustion plant. The system comprises a biomass plant fuelled by wood chips, generating flue gases. These gases are condensed via a double heat exchanger set-up, extracting [...] Read more.
This article outlines the design and performance of a flue gas condensation system integrated with a biomass combustion plant. The system comprises a biomass plant fuelled by wood chips, generating flue gases. These gases are condensed via a double heat exchanger set-up, extracting water and heat to reduce concentrations of CO, CO2, and NOx while releasing gases at a temperature close to ambient temperature. The 100 kW biomass plant operates steadily, consuming 50 kg of wood chips per hour with fuel energy of 18.98 MJ/kg. Post combustion, the gases exit at 430 °C and undergo two-stage cooling. In the first stage, gases are cooled in a high-temperature tube heat exchanger, transferring heat to air. They then enter the second stage, a flue gas/water heat exchanger, recovering sensible and latent thermal energy, which leads to water condensation. Flue gas is discharged at approximately 33 °C. Throughout, parameters like the flue gas temperatures, mass flow, fuel consumption, heat carrier temperatures, and water condensation rates were monitored. The test results show that the system can condense water from flue gas at 75 g/min at 22 °C while reducing pollutant emissions by approximately 20% for CO2, 19% for CO, 30% for NO, and 26% for NOx. Full article
(This article belongs to the Special Issue Advanced Control Strategies for Renewable Energy Systems and Sustainable Development)
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