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Planning and Operation of Distributed Energy Resources in Smart Grids II

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

Deadline for manuscript submissions: 5 May 2025 | Viewed by 11141

Special Issue Editors

Prof. Dr. Stefania Conti

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile e architettura, University of Catania, Catania, Italy
Interests: power systems analysis; renewable sources; integration of distributed generation; smart grids
Dr. Cristina Ventura

E-Mail Website
Guest Editor
DIEEI—Electrical Electronic and Computer Engineering, University of Catania, 95125 Catania, Italy
Interests: photovoltaic systems; photovoltaic and solar forecasting; photovoltaic/thermal systems; floating photovoltaic systems, photovoltaic systems monitoring; fault detection in photovoltaic systems; distributed photovoltaic resources; renewable energy communities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The management of distributed energy resources (DERs) in smart grids is the most promising solution to cope with the steadily increasing demand of electrical energy all over the world, accounting for the requirement of planning a sustainable future from both environmental and economic viewpoints. In fact, the presence of renewable generation injecting power into the electrical networks, as well as the presence of various types of DERs (e.g., electric vehicles, responsive loads, and distributed storage), leads to several critical conditions of unpredictability and insecurity, which require researchers and utilities to develop innovative approaches, such as the smart grid.

Within the smart grid framework, the centralized and distributed generation, transmission, and distribution, as well as the final users, communicate with each other and cooperate so as to enhance the efficiency and reliability of the networks, while new factors introduce security and predictability issues. This can be achieved by using ICT and sensoring technologies to implement intelligent monitoring and control functions. Then, the smart grid concept plays a crucial role in integrating high shares of distributed generators based on variable renewable energies’ sources.

Smart grids require the following challenging characteristics to be implemented effectively: safety, reliability, efficiency, affordability, environmental “cleanliness”, technical and economical optimization, interaction with electricity markets, self-healing ability, and the presence of an appropriate regulatory framework. Therefore, researchers are still involved in many studies and experimental implementations to find solutions to the technical, economic, and regulatory issues.

Any scientific work dealing with the aforementioned topics regarding the planning and operation of smart grids is welcome in this Special Issue.

Prof. Dr. Stefania Conti
Dr. Cristina Ventura
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. 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

  • renewable generation
  • distributed energy resources
  • smart grids
  • microgrids
  • power quality
  • optimal planning and operation
  • smart protections
  • power electronics
  • reliability
  • adequacy

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Published Papers (6 papers)

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Research

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12 pages, 2193 KiB  
Article
Day-Ahead Net Load Forecasting for Renewable Integrated Buildings Using XGBoost
by Spencer Kerkau, Saeed Sepasi, Harun Or Rashid Howlader and Leon Roose
Energies 2025, 18(6), 1518; https://doi.org/10.3390/en18061518 - 19 Mar 2025
Viewed by 309
Abstract
With the large-scale adoption of photovoltaic (PV) systems as a renewable energy source, accurate long-term forecasting benefits both utilities and customers. However, developing forecasting models is challenging due to the need for high-quality training data at fine time intervals, such as 15 and [...] Read more.
With the large-scale adoption of photovoltaic (PV) systems as a renewable energy source, accurate long-term forecasting benefits both utilities and customers. However, developing forecasting models is challenging due to the need for high-quality training data at fine time intervals, such as 15 and 30 min resolutions. While sensors can track necessary data, careful analysis is required, particularly for PV systems, due to weather-induced variability. Well-developed forecasting models could optimize resource scheduling, reduce costs, and support grid stability. This study demonstrates the feasibility of a day-ahead net load forecasting model for a mixed-use office building. The model was developed using multi-year campus load and PV data from the University of Hawaii at Manoa. Preprocessing techniques were applied to clean and separate the data, followed by developing two decoupled models to forecast gross load demand and PV production. A weighted-average function was then incorporated to refine the final prediction. The results show that the model effectively captures day-ahead net load trends across different load shapes and weather conditions. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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14 pages, 1005 KiB  
Article
EOS: Impact Evaluation of Electric Vehicle Adoption on Peak Load Shaving Using Agent-Based Modeling
by William J. Howell, Ziqian Dong and Roberto Rojas-Cessa
Energies 2024, 17(20), 5110; https://doi.org/10.3390/en17205110 - 15 Oct 2024
Cited by 1 | Viewed by 861
Abstract
The increasing adoption of electric vehicles (EVs) by the general population creates an opportunity to deploy the energy storage capability of EVs for performing peak energy shaving in their households and ultimately in their neighborhood grid during surging demand. However, the impact of [...] Read more.
The increasing adoption of electric vehicles (EVs) by the general population creates an opportunity to deploy the energy storage capability of EVs for performing peak energy shaving in their households and ultimately in their neighborhood grid during surging demand. However, the impact of the adoption rate in a neighborhood might be counterbalanced by the energy demand of EVs during off-peak hours. Therefore, achieving optimal peak energy shaving is a product of a sensitive balancing process that depends on the EV adoption rate. In this paper, we propose EOS, an agent-based simulation model, to represent independent household energy usage and estimate the real-time neighborhood energy consumption and peak shaving energy amount of a neighborhood. This study uses Residential Energy Consumption Survey (RECS) and the American Time Use Survey (ATUS) data to model realistic real-time household energy use. We evaluate the impact of the EV adoption rates of a neighborhood on performing energy peak shaving during sudden energy surges. Our findings reveal these trade-offs and, specifically, a reduction of up to 30% of the peak neighborhood energy usage for the optimal neighborhood EV adoption rate in a 1089 household neighborhood. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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19 pages, 4532 KiB  
Article
Modular Microgrid Technology with a Single Development Environment Per Life Cycle
by Teodora Mîndra, Oana Chenaru, Radu Dobrescu and Lucian Toma
Energies 2024, 17(19), 5016; https://doi.org/10.3390/en17195016 - 9 Oct 2024
Viewed by 1276
Abstract
The life cycle of a microgrid covers all the stages from idea to implementation, through exploitation until the end of its life, with a lifespan of around 25 years. Covering them usually requires several software tools, which can make the integration of results [...] Read more.
The life cycle of a microgrid covers all the stages from idea to implementation, through exploitation until the end of its life, with a lifespan of around 25 years. Covering them usually requires several software tools, which can make the integration of results from different stages difficult and may imply costs being hard to estimate from the beginning of a project. This paper proposes a unified platform composed of four modules developed in MATLAB 2022b, designed to assist all the processes a microgrid passes through during its lifetime. This entire platform can be used by a user with low IT knowledge, because it is completed with fill-in-the-blank alone, as a major advantage. The authors detail the architecture, functions and development of the platform, either by highlighting the novel integration of existing MATLAB tools or by developing new ones and designing new user interfaces linked with scripts based on its complex mathematical libraries. By consolidating processes into a single platform, the proposed solution enhances integration, reduces complexity and provides better cost predictability throughout the project’s duration. A proof-of-concept for this platform was presented by applying the life-cycle assessment process on a real-case study, a microgrid consisting of a photovoltaic plant, and an office building as the consumer and energy storage units. This platform has also been developed by involving students within summer internships, as a process strengthening the cooperation between industry and academia. Being an open-source application, the platform will be used within the educational process, where the students will have the possibility to add functionalities, improve the graphical representation, create new reports, etc. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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18 pages, 5100 KiB  
Article
Voltage Frequency Differential Protection Algorithm
by Zdravko Matišić, Tomislav Antić, Juraj Havelka and Tomislav Capuder
Energies 2024, 17(8), 1845; https://doi.org/10.3390/en17081845 - 12 Apr 2024
Viewed by 1124
Abstract
Advancements in new technologies, a reduction in CO2 emissions, and the rising demand for energy are causing a growth in the share of renewable energy sources. In distribution networks, an increasing number of distributed generators (DGs) makes the utility grid’s protection complex [...] Read more.
Advancements in new technologies, a reduction in CO2 emissions, and the rising demand for energy are causing a growth in the share of renewable energy sources. In distribution networks, an increasing number of distributed generators (DGs) makes the utility grid’s protection complex and demanding. Vector surge and rate-of-change-of-frequency are the established anti-islanding protection methods, recognizing that the standard paradigm for protection, involving distributed generation, cannot be set only once but has to be continuously updated following the requirements and changes in the system. One of the requirements is active participation in the preservation of system frequency and voltage, which can be interrupted if the DG trips and disconnects from the utility grid. Anti-islanding protection and spurious tripping can be avoided by implementing new algorithms and techniques. This paper presents a novel protection scheme based on a voltage frequency differential. The proposed algorithm employs remote and local frequency measurements in such a manner that, for the occurrence of a frequency difference, it is assumed that the DG is in an islanding state. In this article, we demonstrate the feasibility of the algorithm through numerical analysis of grid events and laboratory testing emulating real grid-measured values. The test results show that the algorithm is resilient to false tripping for non-islanding events and more reliable than conventional methods in islanding detection. The algorithm can be set to low-frequency differential values, drastically reducing the non-detection zone in any DG type, regardless of its size and voltage level at the point of common coupling. Unlike standard anti-islanding methods, the algorithm supports the ability of the DG to fault-ride through demand. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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Review

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18 pages, 1771 KiB  
Review
A New Electricity Infrastructure for Fostering Urban Sustainability: Challenges and Emerging Trends
by Ettore F. Bompard, Stefania Conti, Marcelo J. Masera and Gian Giuseppe Soma
Energies 2024, 17(22), 5573; https://doi.org/10.3390/en17225573 - 7 Nov 2024
Cited by 1 | Viewed by 1109
Abstract
The energy transition and sustainability are the critical challenges of our time, and cities are at the forefront of this transformation. As key players, these urban centers are pioneering innovative strategies to reduce carbon emissions, enhance energy efficiency, and promote renewable energy sources. [...] Read more.
The energy transition and sustainability are the critical challenges of our time, and cities are at the forefront of this transformation. As key players, these urban centers are pioneering innovative strategies to reduce carbon emissions, enhance energy efficiency, and promote renewable energy sources. Central to the transition is the role of electricity, which acts as a cornerstone in the “cocktail” of sustainable solutions. The development of an efficient and resilient “Electricity City Grid” is essential to support this shift. This article explores the target functions and challenges associated with designing and operating the Smart Electricity City Grid of the future. It delves into the infrastructural costs required for this transition and examines the economic and technical hurdles that must be overcome. Finally, the article looks ahead to the future of research in this field, highlighting the areas that will be crucial for the continued evolution and success of smart urban grids. Through this comprehensive analysis, we aim to suggest a roadmap for cities striving to achieve sustainability through advanced electrical infrastructure. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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22 pages, 1057 KiB  
Review
Impact of Artificial Intelligence on the Planning and Operation of Distributed Energy Systems in Smart Grids
by Paul Arévalo and Francisco Jurado
Energies 2024, 17(17), 4501; https://doi.org/10.3390/en17174501 - 8 Sep 2024
Cited by 13 | Viewed by 5765
Abstract
This review paper thoroughly explores the impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. With the rapid advancement of artificial intelligence techniques such as machine learning, optimization, and cognitive computing, new opportunities are emerging to [...] Read more.
This review paper thoroughly explores the impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. With the rapid advancement of artificial intelligence techniques such as machine learning, optimization, and cognitive computing, new opportunities are emerging to enhance the efficiency and reliability of electrical grids. From demand and generation prediction to energy flow optimization and load management, artificial intelligence is playing a pivotal role in the transformation of energy infrastructure. This paper delves deeply into the latest advancements in specific artificial intelligence applications within the context of distributed energy systems, including the coordination of distributed energy resources, the integration of intermittent renewable energies, and the enhancement of demand response. Furthermore, it discusses the technical, economic, and regulatory challenges associated with the implementation of artificial intelligence-based solutions, as well as the ethical considerations related to automation and autonomous decision-making in the energy sector. This comprehensive analysis provides a detailed insight into how artificial intelligence is reshaping the planning and operation of smart grids and highlights future research and development areas that are crucial for achieving a more efficient, sustainable, and resilient electrical system. Full article
(This article belongs to the Special Issue Planning and Operation of Distributed Energy Resources in Smart Grids II)
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