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The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 10 February 2026 | Viewed by 6627

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Special Issue Editor

Dr. Mahmoud Ghofrani

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School of Science, Technology, Engineering and Mathematics (STEM), University of Washington, Bothell, WA, USA
Interests: power systems operation and planning; renewable energy systems; smart grids; electric vehicles; electricity market
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the energy industry continues to witness advancements in renewable distributed generation (DG), electric vehicles (EVs), energy storage systems, and capacitor banks, it becomes crucial to effectively manage their operational needs, technical characteristics, and economic considerations. Without careful integration and collaboration, we risk complications such as system overloading, equipment failure, voltage deviations, increased losses, and transient stability issues. Therefore, it is imperative that we address these challenges collaboratively to maximize the benefits of these technologies while minimizing their potential risks.

I am therefore pleased to announce a Special Issue that aims to connect researchers from academia and industry, and compile studies that present innovative developments, challenges, and solutions in the field of energy technologies and their integration into electric grids. We invite you to contribute your expertise and insights to this important discussion.

The scope of this Special Issue includes, but is not limited to, the following topics:

Novel optimization algorithms for the operation and planning of smart electric grids with different energy technologies: We encourage researchers to explore novel algorithms and methodologies that can effectively manage the integration of diverse energy technologies into distribution grids. This includes addressing challenges such as load balancing, demand response, and grid stability.
Micro-grids and state-of-the-art methods for their optimization and control: Micro-grids play a crucial role in the integration of energy technologies. We invite researchers to present their work on the optimization and control of micro-grids, including advanced control strategies, energy management systems, and grid-tied and islanded operation modes.
Innovative solutions for the efficient communication of energy technologies: Communication is vital for the seamless integration of energy technologies. We welcome submissions that propose novel communication protocols, network architectures, and data management techniques to enable efficient and reliable communication among different energy technologies.
Policy and regulatory issues and solutions for the seamless integration of energy technologies: The integration of energy technologies requires a supportive policy and regulatory framework. We encourage researchers to explore policy and regulatory challenges and propose solutions that facilitate the seamless integration of energy technologies into distribution grids.
Big data analytics and data privacy for the collaborative operation of energy technologies: With the increasing deployment of energy technologies, there is a growing need for effective data analytics and privacy protection. We invite researchers to present their work on big data analytics, machine learning, and data privacy solutions for the collaborative operation of energy technologies.
Cybersecurity solutions for the safe and reliable operation of electric grids with energy technologies: As the grid becomes more interconnected, it is crucial to ensure cybersecurity. We welcome submissions that address cybersecurity challenges and propose solutions for safeguarding the operation of electric grids with energy technologies.

We believe that, by sharing knowledge and experiences, our understanding of the challenges and opportunities associated with the integration of diverse energy technologies into distribution grids can be enhanced. Your contribution to this Special Issue will be invaluable in advancing the field and shaping the future of energy systems.

Dr. Mahmoud Ghofrani
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

smart electric grids
micro-grids
renewable energy
electric vehicles
power systems
energy storage systems
energy management
optimization algorithms
policy frameworks
big data analytics
cybersecurity solutions

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Published Papers (8 papers)

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Research

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24 pages, 4843 KB

Open AccessArticle

Enhancing Smart Grid Reliability Through Data-Driven Optimisation and Cyber-Resilient EV Integration

by Muhammed Cavus, Huseyin Ayan, Mahmut Sari, Osman Akbulut, Dilum Dissanayake and Margaret Bell

Energies 2025, 18(17), 4510; https://doi.org/10.3390/en18174510 - 25 Aug 2025

Cited by 1 | Viewed by 645

Abstract

This study presents a novel cyber-resilient, data-driven optimisation framework for real-time energy management in electric vehicle (EV)-integrated smart grids. The proposed framework integrates a hybrid optimisation engine—combining genetic algorithms and reinforcement learning—with a real-time analytics module to enable adaptive scheduling under uncertainty. It accounts for dynamic electricity pricing, EV mobility patterns, and grid load fluctuations, dynamically reallocating charging demand in response to evolving grid conditions. Unlike existing GA/RL schedulers, this framework uniquely integrates adaptive optimisation with resilient forecasting under incomplete data and lightweight blockchain-inspired cyber-defence, thereby addressing efficiency, accuracy, and security simultaneously. To ensure secure and trustworthy EV–grid communication, a lightweight blockchain-inspired protocol is incorporated, supported by an intrusion detection system (IDS) for cyber-attack mitigation. Empirical evaluation using European smart grid datasets demonstrates a daily peak demand reduction of 9.6% (from 33 kWh to 29.8 kWh), with a 27% decrease in energy delivered at the original peak hour and a redistribution of demand that increases delivery at 19:00 h by nearly 25%. Station utilisation became more balanced, with weekly peak normalised utilisation falling from 1.0 to 0.7. The forecasting module achieved a mean absolute error (MAE) of 0.25 kWh and a mean absolute percentage error (MAPE) below 20% even with up to 25% missing data. Among tested models, CatBoost outperformed LightGBM and XGBoost with an RMSE of 0.853 kWh and

R^{2}

of 0.416. The IDS achieved 94.1% accuracy, an AUC of 0.97, and detected attacks within 50–300 ms, maintaining over 74% detection accuracy under 50% novel attack scenarios. The optimisation runtime remained below 0.4 s even at five times the nominal dataset scale. Additionally, the study outlines a conceptual extension to support location-based planning of charging infrastructure. This proposes the alignment of infrastructure roll-out with forecasted demand to enhance spatial deployment efficiency. While not implemented in the current framework, this forward-looking integration highlights opportunities for synchronising infrastructure development with dynamic usage patterns. Collectively, the findings confirm that the proposed approach is technically robust, operationally feasible, and adaptable to the evolving demands of intelligent EV–smart grid systems. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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25 pages, 2100 KB

Open AccessArticle

Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives

by Nuno Souza e Silva and Paulo Ferrão

Energies 2025, 18(15), 4107; https://doi.org/10.3390/en18154107 - 2 Aug 2025

Viewed by 373

Abstract

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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20 pages, 2728 KB

Open AccessArticle

A Novel Technical Framework for Colombia’s Distribution System Operator with Distributed Energy Resources Integration

by Eduardo Gómez-Luna, Jonathan A. Tariacuri, Jorge De La Cruz and Juan C. Vasquez

Energies 2025, 18(11), 2881; https://doi.org/10.3390/en18112881 - 30 May 2025

Cited by 1 | Viewed by 819

Abstract

This paper presents a thorough examination of the technical requirements for a new Distribution System Operation (DSO) scheme in Colombia. This study contextualizes these requirements to consider local particularities by looking at national and international standards and models relevant to DSO. This study aims to align the technical requirements to the DSO technologies that offer the greatest advantages (real-time data readings to automate commercial cycle, suspension and reconnection of the service, improving reliability and quality of power supply, and environmental benefits) and the fewest implementation obstacles. Today, an electrical operator can become more proactive by integrating technologies such as advanced metering infrastructure (AMI), distributed energy resources (DER), microgrids, and advanced distribution automation (ADA). This study will provide a structured framework for the implementation of a cutting-edge DSO technology in order to assist Colombia’s energy sector in becoming more dynamic and efficient with a smarter and more active electricity distribution system. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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21 pages, 3874 KB

Open AccessArticle

Supply of MV Island with High-Penetration of Prosumer Renewable Energy Sources

by Krzysztof Dobrzynski, Zbigniew Lubośny, Jacek Klucznik, Paweł Bućko, Sławomir Noske, Mirosław Matusewicz, Michał Brodzicki, Maciej Klebba and Arkadiusz Frącz

Energies 2025, 18(10), 2625; https://doi.org/10.3390/en18102625 - 19 May 2025

Viewed by 528

Abstract

The rapid development of prosumer renewable energy sources (RESs) observed in Poland in recent years causes problems in distribution networks such as current amplitude and voltage asymmetry increases, power and energy loss increases, and reverse power flows, and related are voltage control problems, deterioration of energy quality, etc. Moreover, in the case of planned repair/maintenance works in the network and the need to supply energy consumers in an islanded MV grid, the problem of the correct operation of such a subsystem appears. This occurs when the power production by the prosumers’ energy sources at a given moment exceed the power consumption. In such a case, reverse power flows occur in MV/LV transformers, i.e., from the LV network to the MV network. This causes reverse power flow to the diesel generator, leading to its shutdown and, in extreme cases, to damage. The solution to this problem is to use a mobile system equipped with energy storage in addition to a diesel generator and an LV/MV transformer. An additional problem in the case of using a mobile system (diesel generator) to power an MV island is the islanded MV network grounding. Grid islanding changes the earth fault current and electric shock voltages. In general, MV networks in Poland operate as compensated, i.e., grounding transformers are used, the star point of which is grounded by a compensation choke. Unfortunately, in the case of powering an MV island from a mobile system, there is no real possibility of grounding the star point of the LV/MV transformer used there. This article proposes an algorithm of a diesel generator with an energy storage selection, including electric shock protection requirements verification, for the use in suppling energy via an islanded MV network. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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16 pages, 1689 KB

Open AccessArticle

Smart Grids and Sustainability: The Impact of Digital Technologies on the Energy Transition

by Paola Campana, Riccardo Censi, Roberto Ruggieri and Carlo Amendola

Energies 2025, 18(9), 2149; https://doi.org/10.3390/en18092149 - 22 Apr 2025

Cited by 3 | Viewed by 2559

Abstract

Smart Grids (SG) represent a key element in the energy transition, facilitating the integration of renewable and conventional energy sources through the use of advanced digital technologies. This study analyzes the main research trends related to SG, energy efficiency, and the role of Artificial Intelligence (AI) and the Internet of Things (IoT) in smart energy management. Following the PRISMA protocol, 179 relevant academic articles indexed in the Scopus database were selected and analyzed using VOSviewer software, version 1.6.20, to identify the main thematic clusters. The results reveal a converging research focus on energy flow optimization, renewable energy integration, and the adoption of digital technologies—including cybersecurity solutions—to ensure grid efficiency, security, and resilience. The study confirms that digitalization acts as a key enabler for building a more sustainable and reliable energy system, aligned with the objectives of the European Union and the United Nations 2030 Agenda. The contribution of this work lies in its integrated approach to the analysis of digital technologies, linking the themes of efficiency, resilience, and infrastructure security, in order to provide valuable insights for future research and sustainable energy policy development. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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23 pages, 1317 KB

Open AccessFeature PaperArticle

Sensitivity Analysis of Distribution Network Reconfiguration Optimization for Electric Vehicle and Renewable Distributed Generator Integration

by Mahmoud Ghofrani

Energies 2025, 18(8), 1903; https://doi.org/10.3390/en18081903 - 9 Apr 2025

Cited by 1 | Viewed by 502

Abstract

Distribution networks have faced significant efficiency and reliability challenges, balancing the recent integration of electric vehicles (EVs) and renewable distributed generators (DGs). This study proposes a reconfiguration optimization of the distribution system by adjusting the status of switches within the network. This approach aims to minimize power losses and enhance overall operational efficiency. To model the variability of wind and solar DGs, probability distribution functions (PDFs) are employed, which allow for a more accurate representation of their performance. Additionally, stochastic models and Monte Carlo Simulation (MCS) are utilized to generate various scenarios that reflect real-world conditions, including the charging and discharging behaviors of EVs. A sensitivity analysis is conducted to evaluate the effectiveness of our proposed reconfiguration strategy across different levels of EV and DG penetration. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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Review

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33 pages, 3171 KB

Open AccessReview

Advances in Energy Storage, AI Optimisation, and Cybersecurity for Electric Vehicle Grid Integration

by Muhammed Cavus, Huseyin Ayan, Margaret Bell and Dilum Dissanayake

Energies 2025, 18(17), 4599; https://doi.org/10.3390/en18174599 - 29 Aug 2025

Viewed by 454

Abstract

The integration of electric vehicles (EVs) into smart grids (SGs) is reshaping both energy systems and mobility infrastructures. This review presents a comprehensive and cross-disciplinary synthesis of current technologies, methodologies, and challenges associated with EV–SG interaction. Unlike prior reviews that address these aspects in isolation, this work uniquely connects three critical pillars: (i) the evolution of energy storage technologies, including lithium-ion, second-life, and hybrid systems; (ii) optimisation and predictive control techniques using artificial intelligence (AI) for real-time energy management and vehicle-to-grid (V2G) coordination; and (iii) cybersecurity risks and post-quantum solutions required to safeguard increasingly decentralised and data-intensive grid environments. The novelty of this review lies in its integrated perspective, highlighting how emerging innovations, such as federated AI models, blockchain-secured V2G transactions, digital twin simulations, and quantum-safe cryptography, are converging to overcome existing limitations in scalability, resilience, and interoperability. Furthermore, we identify underexplored research gaps, such as standardisation of bidirectional communication protocols, regulatory inertia in V2G market participation, and the lack of unified privacy-preserving data architectures. By mapping current advancements and outlining a strategic research roadmap, this article provides a forward-looking foundation for the development of secure, flexible, and grid-responsive EV ecosystems. The findings support policymakers, engineers, and researchers in advancing the technical and regulatory landscape necessary to scale EV–SG integration within sustainable smart cities. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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Other

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44 pages, 1304 KB

Open AccessSystematic Review

Securing the Electrified Future: A Systematic Review of Cyber Attacks, Intrusion and Anomaly Detection, and Authentication in Electric Vehicle Charging Infrastructure

by Lukasz Pawlik, Jacek Lukasz Wilk-Jakubowski, Pawel Tomasz Grabski and Grzegorz Wilk-Jakubowski

Energies 2025, 18(18), 4847; https://doi.org/10.3390/en18184847 - 11 Sep 2025

Abstract

The growing popularity of electric vehicles (EVs) necessitates a robust and secure charging infrastructure. This review article analyzes the current state of cybersecurity challenges within EV charging ecosystems, focusing on vulnerabilities affecting charging stations, communication protocols, and grid integration technologies such as vehicle-to-grid (V2G). Based on a systematic literature review, common cyber threats are categorized, including data manipulation, authentication bypass, infrastructure failures, and attacks on backend systems and the power grid. Furthermore, this paper synthesizes existing and emerging risk mitigation strategies, encompassing intrusion detection systems (IDS), secure communication protocols, authentication frameworks, and anomaly detection techniques utilizing machine learning and blockchain technologies. By analyzing literature published between 2017 and 2024, this study aims to provide a comprehensive overview of cybersecurity issues that are critical to ensuring the resilience and reliability of the evolving EV charging infrastructure. The scope of this review is centered specifically on cyber attacks, intrusion and anomaly detection, and authentication mechanisms within EV charging infrastructures, rather than on the broader cybersecurity domain. Full article

(This article belongs to the Special Issue The Future of Energy Systems: Integration of Energy Technologies in Distribution Grids)

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