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

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

Deadline for manuscript submissions: closed (5 May 2026) | Viewed by 7827

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Prof. Dr. Jesus C. Hernandez

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Guest Editor

Electrical Engineering Department, University of Jaen, Campus Las Lagunillas, S/N, 23071 Jaen, Spain
Interests: power electronics; renewable systems; microgrids; electric vehicles; power quality; power systems simulation; metaheuristic optimization
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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 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-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 (10 papers)

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Research

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16 pages, 9270 KB

Open AccessArticle

Performance of Coloured Building-Integrated Photovoltaic Modules: A Three-Colour East-Oriented Façade

by Nuria Martín-Chivelet, José Cuenca, Miguel Alonso-Abella, Manuel Rodrigo, Carlos Sanz-Saiz, Jesús Polo and Zayd Valdez

Energies 2026, 19(10), 2367; https://doi.org/10.3390/en19102367 - 15 May 2026

Viewed by 204

Abstract

The market for coloured photovoltaic modules offers a key opportunity for building-integrated photovoltaics (BIPV), as it enables more aesthetic and seamless integration into architecture. This study investigates how three common BIPV colours—anthracite, green, and terracotta—affect the performance of a BIPV ventilated façade. It presents a year-long field comparison, including thermal modelling and residual spectral loss estimation, of three screen-printed coloured BIPV strings installed on an east-facing ventilated façade, at the CIEMAT research centre in Madrid, Spain. Although anthracite modules exhibit the highest efficiency under standard test conditions (STC), green modules achieve the best performance ratio (PR) due to their lower spectral and thermal impacts. Results indicate that system design factors—such as façade orientation, module positioning and rear ventilation—significantly influence thermal and electrical performance. In particular, changes in solar spectral irradiance can have a strong impact on the performance of coloured modules, mainly due to their distinct spectral reflectance characteristics. This effect is especially relevant for reddish modules mounted on east- and west-facing façades, which, on clear days, receive sunlight with spectra shifted toward the near-infrared (NIR) region compared with midday conditions, which are closer to the standard AM1.5G solar spectrum. Prior optical characterisation, particularly spectral reflectance measurements, is therefore essential to accurately assess and predict the performance of coloured modules under real operating conditions. 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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21 pages, 3896 KB

Open AccessArticle

Investigating the Participation of Embedded VSC-HVDC Systems in Frequency Regulation During Post-Splitting Events via a Coordinated Supplementary Control Layer

by Mohammad Qawaqneh, Gaetano Zizzo, Antony Vasile, Liliana Mineo, Angelo L’Abbate and Lorenzo Carmine Vitulano

Energies 2026, 19(9), 2034; https://doi.org/10.3390/en19092034 - 23 Apr 2026

Viewed by 480

Abstract

Synchronous Alternating Current (AC) power systems are increasingly supported by embedded High-Voltage Direct Current (HVDC) links to enhance operational flexibility and ensure security of supply. However, the loss of High-Voltage Alternating Current (HVAC) interconnections in these synchronous areas may lead to transmission network splitting, posing serious challenges to frequency stability due to the reduction in overall system inertia and stiffness. In this paper, a supplementary control layer is proposed to enable embedded HVDC systems, particularly those based on modern Voltage Source Converters (VSCs), to support frequency stability under post-splitting conditions. The proposed control strategy combines Angle-Difference Control (ADC), Frequency-Difference Control (FDC), and feedforward action, enabling fast and coordinated active-power modulation. A single-bus, dynamic multi-area Load Frequency Control (LFC) model is developed, combining the regulation of thermal units, Renewable Energy Sources’ (RESs’) Fast Frequency Response (FFR) with Synthetic Inertia (SI), and VSC-HVDC modulation. The effectiveness of the proposed control layer is demonstrated by applying it to the East Tyrrhenian Link (ETL), an embedded VSC-HVDC interconnection connecting Sicily with the mainland of Italy, under a post-splitting low-inertia condition in which Sicily operates as an islanded synchronous system, i.e., after losing synchronism with the mainland of Italy, in a 2030 scenario condition. The simulation results demonstrate that the proposed controller enables embedded VSC-HVDC systems to actively participate in post-splitting frequency containment and damping, as well as coordinated active power reallocation, thereby enhancing overall system stability and resilience. 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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41 pages, 4529 KB

Open AccessArticle

Probabilistic Modeling of Available Transfer Capability with Dynamic Transmission Reliability Margin for Renewable Energy Export and Integration

by Uchenna Emmanuel Edeh, Tek Tjing Lie and Md Apel Mahmud

Energies 2026, 19(8), 1864; https://doi.org/10.3390/en19081864 - 10 Apr 2026

Viewed by 1161

Abstract

This paper develops a probabilistic Available Transfer Capability (ATC) framework that quantifies export headroom for renewables across transmission-distribution interfaces under time-varying uncertainty. Static transmission reliability margins can unnecessarily curtail exports. A dynamic transmission reliability margin (TRM) is embedded within ATC using rolling window statistics and adaptive confidence factor scheduling to release capacity in calm periods and tighten margins during volatile transitions. Uncertainty is modeled as net nodal power imbalance variability from load and renewable deviations, together with stochastic thermal limit fluctuations. Correlated multivariate scenarios are generated via Latin Hypercube Sampling with Iman-Conover correlation preservation and propagated through full AC power flow analysis. Validation on the IEEE 39-bus system and New Zealand’s HVDC inter-island corridor recovers 93.31 MW of usable transfer capacity on the IEEE system relative to the pooled Monte Carlo P95 constant-margin baseline, with 78.11 MW attributable to rolling window volatility tracking and 15.20 MW to adaptive confidence factor scheduling, and 59.51 MW (+7.6%) on the New Zealand corridor relative to the corresponding pooled Monte Carlo P95 baseline, with the gain arising primarily from rolling window volatility tracking. Relative to a 95% one-sided reliability target, achieved coverage is 93.9% for IEEE and 91.8% for New Zealand, translating into increased export headroom and reduced curtailment. 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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23 pages, 1818 KB

Open AccessArticle

Design and Performance Evaluation of a Hybrid Renewable Energy System Integrating Wind, Diesel Generators, and Battery Storage for Remote Communities

by Samira Salari, Amin Etminan and Mohsin Jamil

Energies 2026, 19(7), 1676; https://doi.org/10.3390/en19071676 - 29 Mar 2026

Cited by 1 | Viewed by 636

Abstract

Climate change poses an urgent challenge to Canada’s sustainable development. The country experiences increasing extreme weather events, rising temperatures, and pressures on energy systems—particularly in remote northern regions. In Newfoundland and Labrador, isolated communities are vulnerable because reliance on diesel-based electricity increases greenhouse gas emissions, energy costs, and environmental risks, highlighting the need for resilient energy solutions. This study uses a systematic methodology combining literature review, local energy demand data, and site-specific wind resources to design and optimize hybrid renewable energy systems (HRESs) for Makkovik. It employs HOMER Pro and the Monte Carlo method to evaluate uncertainties in cost, fuel consumption, and renewable fraction. The objectives are to quantify how renewable integration can reduce emissions, improve energy reliability, and support sustainable development in remote communities. The novelty lies in combining location-specific modeling with probabilistic Monte Carlo analysis and providing robust, system-level insights into environmental and economic outcomes while guiding climate-resilient energy planning. The proposed HRES significantly mitigates climate change impacts, reducing annual CO₂ emissions from 72,500 kg/year to 15,190 kg/year. Monte Carlo analysis indicates economic feasibility with a net present cost of $14.5 million, a levelized cost of electricity of 0.256 $/kWh, and diesel consumption reduced from 29,970 L/year to 5854 L/year. Wind energy provides 99.6% of total annual electricity, ensuring a high renewable fraction and reliable power, enhancing energy resilience and adaptation potential. This study demonstrates that a well-designed hybrid renewable energy system can deliver measurable emission reductions, economic feasibility, and enhanced energy resilience. It supports sustainable development and climate change mitigation in remote Canadian communities. 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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30 pages, 8792 KB

Open AccessArticle

Incorporating Renewable Generation Uncertainty Into Multi-Objective Dispatch Optimization

by Eduardo Conde Lázaro, Alberto Ramos Millán, Pablo Reina Peral and Carlos Enrique Vázquez Martínez

Energies 2026, 19(2), 545; https://doi.org/10.3390/en19020545 - 21 Jan 2026

Viewed by 295

Abstract

This article analyzes an electrical system based on the IEEE-57 bus case, which integrates thermal and wind generation to meet hourly demand. Using the previous day’s wind forecasts as firm market bids, the optimal Pareto frontier for thermal dispatch is calculated, balancing total cost and emissions. The system operator selects a dispatch point based on the desired cost–emissions ratio. To reflect real-world uncertainty, the study incorporates statistical deviations in actual wind production derived from historical data. For each deviation scenario, new optimal thermal dispatch curves are generated. This approach allows for preventive scheduling across the range of expected wind deviations and supports real-time adjustments through mechanisms such as redispatching, intraday markets, or secondary/tertiary regulation. 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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16 pages, 1524 KB

Open AccessArticle

Data-Driven Estimation of Transmission Loss Coefficients via Linear and Quadratic Programming Under Linear Constraints

by Oscar Danilo Montoya, Carlos Adrián Correa-Flórez, Walter Gil-González, Luis Fernando Grisales-Noreña and Jesús C. Hernández

Energies 2026, 19(2), 405; https://doi.org/10.3390/en19020405 - 14 Jan 2026

Cited by 1 | Viewed by 519

Abstract

This paper presents a robust data-driven methodology for estimating transmission loss coefficients (B-coefficients) in power systems using linear and quadratic programming (LP and QP), both of which belong to the family of convex optimization models. The first model employs a linear objective function with linear constraints, ensuring computational efficiency for simpler scenarios. The second model utilizes a quadratic objective function, also under linear constraints, to better capture more complex nonlinear relationships. By framing the estimation problem as a parameter identification task, both methodologies minimize the cost functions that quantify the mismatch between measured and modeled power losses. By considering a broad range of operational scenarios, our approach effectively captures the stochastic behavior inherent in power system operations. The effectiveness of both the LP and QP models is validated in terms of their ability to accurately extract physically meaningful B-coefficients from diverse simulation datasets. This study underscores the potential of integrating linear and quadratic programming as powerful and scalable tools for data-driven parameter estimation in modern power systems, especially in environments characterized by uncertainty or incomplete information. 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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22 pages, 8029 KB

Open AccessArticle

Early-Stage Fault Diagnosis for Batteries Based on Expansion Force Prediction

by Liye Wang, Yong Li, Yuxin Tian, Jinlong Wu, Chunxiao Ma, Lifang Wang and Chenglin Liao

Energies 2025, 18(24), 6619; https://doi.org/10.3390/en18246619 - 18 Dec 2025

Viewed by 609

Abstract

With the continuous expansion of the electric vehicle market, lithium-ion batteries have also been rapidly developed, but this has brought about concerns over the safety of lithium-ion batteries. Research on the correlation mechanism between the expansion and safety of lithium-ion batteries is a key step in the construction of a battery life cycle safety evaluation system. In this paper, the physicochemical mechanism of early safety faults in batteries was analyzed from three dimensions of electricity, heat, and force. The interactions of electrochemical side reactions, thermal runaway chain reactions, and mechanical fault mechanisms were analyzed, and the core induction of early safety risk was explored. A battery coupling model based on electrical, thermal, and mechanical dimensions was built, and the accuracy of the coupling model was verified by a variety of test conditions. Based on the coupling model, the stress distribution of the battery under different safety boundary conditions was simulated, and then the average expansion force of the battery surface was calculated through the stress distribution results. Through this process, a multi-parameter database based on the test and simulation data was obtained. According to the data of battery parameters at different times, an early safety classification method based on the battery expansion force was proposed, and a classification model between battery dimension data and safety level was proposed based on the nonlinear dynamic sparse regression method, and the classification accuracy was validated. From the perspective of fault warning, by establishing a multi-physical coupling model of electrical, thermal, and mechanical fields, the space-time evolution law of battery expansion under different working conditions can be dynamically monitored, and the fault criterion based on the expansion force can be established accordingly to provide quantitative indicators for safety risk classification warnings, and improve the battery’s reliability and durability. 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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20 pages, 3390 KB

Open AccessEditor’s ChoiceArticle

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

Cited by 3 | Viewed by 1509

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 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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Review

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17 pages, 1167 KB

Open AccessReview

Environmental and Operational Factors That Affect the Performance of a Photovoltaic System

by Ewa Klugmann-Radziemska

Energies 2026, 19(3), 602; https://doi.org/10.3390/en19030602 - 23 Jan 2026

Cited by 1 | Viewed by 559

Abstract

Photovoltaic installations are becoming an increasingly popular source of electricity around the world. The decision on where and how to install the modules and their location is made at the stage of building the installation and is crucial for obtaining the most beneficial effects of its operation. The choice of installation location and its geometry directly influence the following aspects, which determine maximum efficiency and thus economic benefits: solar irradiance, working cell temperature, shading, dust and soiling. Factors that have an unfavorable impact on the efficiency of a photovoltaic installation can be divided into those that should be taken into account at the design stage, such as the correct orientation and angle of inclination of the modules, and those that will play an important role during the use of the system: contamination of the front surface of the modules. This article discusses the impact of these factors and their importance for the proper operation of a photovoltaic installation. 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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17 pages, 267 KB

Open AccessReview

Graphene Nanoplatelets for Advanced Energy Storage Applications

by Aleksandra Tatara and Ewa Klugmann-Radziemska

Energies 2025, 18(23), 6326; https://doi.org/10.3390/en18236326 - 1 Dec 2025

Cited by 1 | Viewed by 1003

Abstract

Graphene nanoplatelets (GNPs) represent a promising class of carbon nanomaterials bridging the gap between graphite and monolayer graphene. Their unique combination of high electrical conductivity, large specific surface area, mechanical strength, and chemical stability makes them attractive for advanced energy storage applications. This review summarizes recent developments in the synthesis, functionalization, characterization, and application of GNPs in supercapacitors, batteries, and hybrid systems. The influence of key structural parameters—such as flake thickness, lateral size, surface chemistry, and defect density—on electrochemical performance is discussed, highlighting structure–property correlations. Particular emphasis is placed on scalable production methods, including mechanical, liquid-phase, and electrochemical exfoliation, as well as edge functionalization and heteroatom doping strategies. Comparative analyses show that GNP-based electrodes can significantly improve specific capacitance, conductivity, and cycling stability, especially when used in composites with polymers or metal oxides. The review also addresses current challenges related to aggregation, dispersion, standardization, and environmental impact. Finally, prospects for the development of sustainable, low-emission GNP production and its integration into next-generation energy storage systems are outlined. 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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