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Renewable Energy Development in Distribution Networks: Optimization, Assessment and Design...
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Renewable Energy Development in Distribution Networks: Optimization, Assessment and Design of Renewable Plants

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: 25 October 2025 | Viewed by 985

Special Issue Editor

Dr. Jesus C. Hernandez

E-Mail Website
Guest Editor
Electrical Engineering Department, University of Jaen, Campus Las Lagunillas, 23071 Jaen, Spain
Interests: power electronics; renewable systems; microgrids; electric vehicles; power quality; power systems simulation; metaheuristic optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions to a Special Issue of Energies, titled “Renewable Energy Development in Distribution Networks: Optimization, Assessment and Design of Renewable Plants”.

Electrical distribution networks have been rapidly transformed by the significant  integration of renewable energy sources, energy storage systems, and active power consumers. These changes require new methodologies to optimize, assess, and design these grids and renewable plants. Power electronics has emerged as a key technology in the conversion and control of electrical power in multiple renewable applications.

The main aim of this Special Issue is to seek high-quality contributions that address current issues related to more sustainable, safer, and more resilient distribution networks. Topics of interest include but are not limited to the following:

  • Solar, wind, and emerging generation technologies;
  • Control method of power electronic converters;
  • Optimization of operation of power systems;
  • Energy storage technologies;
  • Multi-phase distribution networks;
  • Direct current distribution networks;
  • Electric distributed systems;
  • Voltage stability and optimal line flow analysis;
  • Application of the IoT and/or AI for distribution networks.

Dr. Jesus C. Hernandez
Guest Editor

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. Energies 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 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

  • distribution system modelling
  • optimization algorithms
  • renewable energies
  • distributed generation
  • systems and control for power electronic converters
  • hybrid AC/DC systems
  • distribution system planning and operation
  • IoT
  • AI

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Published Papers (1 paper)

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Research

20 pages, 3390 KB  
Article
Pattern-Aware BiLSTM Framework for Imputation of Missing Data in Solar Photovoltaic Generation
by Minseok Jang and Sung-Kwan Joo
Energies 2025, 18(17), 4734; https://doi.org/10.3390/en18174734 - 5 Sep 2025
Viewed by 718
Abstract
Accurate data on solar photovoltaic (PV) generation is essential for the effective prediction of energy production and the effective management of distributed energy resources (DERs). Such data also plays a crucial role in ensuring the operation of DERs within modern power distribution systems [...] Read more.
Accurate data on solar photovoltaic (PV) generation is essential for the effective prediction of energy production and the effective management of distributed energy resources (DERs). Such data also plays a crucial role in ensuring the operation of DERs within modern power distribution systems is both safe and economical. Missing values, which may be attributed to faults in sensors, communication failures or environmental disturbances, represent a significant challenge for distribution system operators (DSOs) in terms of performing state estimation, optimal dispatch, and voltage regulation. This paper proposes a Pattern-Aware Bidirectional Long Short-Term Memory (PA-BiLSTM) model for solar generation imputation to address this challenge. In contrast to conventional convolution-based approaches such as the Convolutional Autoencoder and U-Net, the proposed framework integrates a 1D convolutional module to capture local temporal patterns with a bidirectional recurrent architecture to model long-term dependencies. The model was evaluated in realistic block–random missing scenarios (1 h, 2 h, 3 h, and 4 h gaps) using 5 min resolution PV data from 50 sites across 11 regions in South Korea. The numerical results show that the PA-BiLSTM model consistently outperforms the baseline methods. For example, with a time gap of one hour, it achieves an MAE of 0.0123, an R2 value of 0.98, and an average MSE, with a maximum reduction of around 15%, compared to baseline models. Even under 4 h gaps, the model maintains robust accuracy (MAE = 0.070, R2 = 0.66). The results of this study provide robust evidence that accurate, pattern-aware imputation is a significant enabling technology for DER-centric distribution system operations, thereby ensuring more reliable grid monitoring and control. Full article
(This article belongs to the Special Issue Renewable Energy Development in Distribution Networks: Optimization, Assessment and Design of Renewable Plants)
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