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Processes
Special Issues
Power Converters for Renewable Energy Conversion and Industrial Applications
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Power Converters for Renewable Energy Conversion and Industrial Applications

A Special Issue of Processes (ISSN 2227-9717) belonging to the section "Energy Systems".

Deadline for manuscript submissions: 15 February 2027 | Viewed by 924

Editors

Prof. Dr. Andrés A. Valdez-Fernández

E-Mail Website
Guest Editor
Facultad Ciencias, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico
Interests: analysis; modeling and control design and fault diagnosis of active power filters; inverters; rectifiers; renewable energy systems; e-mobility systems
Prof. Dr. Juan Segundo Ramírez

E-Mail Website
Guest Editor
Facultad Ingenieria, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico
Interests: power systems modeling and stability; harmonic stability; electromagnetic transient stability; EMT modeling and simulation; real time simulation; harmonic modeling and analysis

Special Issue Information

Dear Colleagues,

The growing demand for renewable energy technologies, electromobility, smart power systems and modern industrial applications has accelerated the development of advanced energy conversion solutions. In this context, renewable energy applications such as photovoltaic generation, energy storage platforms, microgrids and electric vehicles require power converter topologies capable of operating under dynamic conditions while ensuring stability, reliability, power quality and grid compatibility. Furthermore, recent advances in modulation schemes, modeling, control techniques, fault diagnoses and optimization techniques have significantly expanded the capabilities and performance of modern power conversion systems.

This Special Issue on “Power Converters for Renewable Energy Conversion and Industrial Applications” seeks high-quality works focusing on advanced converter topologies, modulation schemes, control strategies, fault diagnosis techniques and grid integration technologies that improve the capabilities and performance in renewable energy applications and modern industrial applications. Topics include, but are not limited to, the following:

  • Electromobility and electric vehicle power conversion systems
  • Photovoltaic energy conversion systems
  • Conversion systems for grid integration
  • Power inverter topologies
  • Modeling, control design and fault diagnosis
  • DC–DC power conversion techniques
  • Energy storage integration and management
  • Reliability, monitoring and protection of power electronic systems
  • Grid interactions of grid-connected converters
  • Harmonic stability in converter-dominated power systems
  • Electromagnetic transient stability in converter-dominated power systems
  • Grid-forming and grid-following converter-based renewable energy systems
  • Industrial power electronic systems

Researchers from academia, industry and research institutions are invited to contribute manuscripts that advance the state of the art in renewable energy conversion technologies and power electronics applications.

Thank you and we hope you consider participating in this Special Issue.

Prof. Dr. Andrés A. Valdez-Fernández
Prof. Dr. Juan Segundo Ramírez
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes 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

  • electromobility
  • photovoltaic energy conversion
  • conversion systems for grid integration
  • power inverter topologies
  • modeling, control design and fault diagnosis
  • DC–DC power conversion
  • stability
  • oscillations
  • industrial applications

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

30 pages, 7908 KB  
Article
AI-Driven Cost Estimation in Shipbuilding: A Hybrid Framework Integrating PSO and XGBoost
by Yifan Su, Guanghua Xu and Jing Yang
Processes 2026, 14(17), 2792; https://doi.org/10.3390/pr14172792 - 31 Aug 2026
Viewed by 347
Abstract
Accurate shipbuilding cost estimation is important for project quotation, budget preparation, cost control, and operational decision-making. This study proposes an AI-driven hybrid framework for shipbuilding cost estimation by integrating particle swarm optimization (PSO) with the extreme gradient boosting (XGBoost) algorithm. The empirical dataset [...] Read more.
Accurate shipbuilding cost estimation is important for project quotation, budget preparation, cost control, and operational decision-making. This study proposes an AI-driven hybrid framework for shipbuilding cost estimation by integrating particle swarm optimization (PSO) with the extreme gradient boosting (XGBoost) algorithm. The empirical dataset consists of 51 conventional vessels constructed by a shipyard between 2020 and 2024. Based on the characteristics of these vessels and their construction environment, 11 internal and external cost-influencing factors were selected as input variables. The dataset was divided into a training set and a test set at a ratio of 85% to 15%. The PSO-XGBoost model was compared with the conventional XGBoost model using R2 and MAPE. On the test set, the proposed model achieved an R2 of 0.8718 and a MAPE of 3.87%, compared with 0.8474 and 4.15%, respectively, for the conventional XGBoost model. SHAP analysis was further employed to examine the direction and relative contribution of the influencing factors, thereby improving the interpretability of the estimation results. Case-based validation using different conventional ship types further demonstrates the practical feasibility of the proposed framework. The findings indicate that PSO-based hyperparameter optimization can improve the predictive performance of XGBoost and provide interpretable decision support for shipbuilding cost management. Full article
(This article belongs to the Special Issue Power Converters for Renewable Energy Conversion and Industrial Applications)
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