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Planning, Operation and Control of Microgrids: 2nd Edition
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Planning, Operation and Control of Microgrids: 2nd Edition

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

Deadline for manuscript submissions: 15 July 2025 | Viewed by 4110

Special Issue Editor

Prof. Dr. Federico Martin Serra

E-Mail Website
Guest Editor
Laboratory of Automatic Control (LCA), Faculty of Engineering and Agricultural Sciences, National University of San Luis—CONICET, Villa Mercedes, San Luis 5730, Argentina
Interests: modeling and advanced control of power converters in applications of microgrids, electric vehicles, and renewable energy conversion systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The implementation of microgrids has been promoted by recent actions aimed at reducing the negative environmental impact of conventional electricity generation and inefficient energy consumption. These microgrids have allowed for the decentralization of the conventional power system and provision of energy to isolated regions. Additionally, microgrids are now being used in applications such as electric mobility and aerospace systems. This has made microgrids a challenging research topic, leading to the development of new topologies, management systems, control strategies, monitoring, and protection systems, and more. However, in order to achieve widespread use of microgrids, it is necessary to research and develop new technologies that increase their efficiency, reliability, flexibility, and adaptability.

This Special Issue aims to present recent developments in the fields of planning, operation, and control of microgrids and their applications. These topics include, but are not limited to:

  • Microgrid optimization, planning, and control;
  • Modeling, analysis, and control of DC and AC microgrids based on renewable energy sources;
  • Analysis and operation of grid-connected, isolated, and hybrid microgrids;
  • Modeling and control of low-power and high-power converters for microgrids and smart grid applications;
  • Integration of microgrids into the electric power system;
  • Integration of electric vehicles in microgrids;
  • Design of control and management strategies for microgrids and smart grids;
  • Integration of energy storage systems based on batteries, supercapacitors, and superconducting coils in microgrids;
  • Optimization algorithms for energy management and intelligent control of microgrids;
  • Ancillary services of microgrids;
  • Diagnostics, maintenance, reliability, vulnerability, and self-healing of microgrids.

Prof. Dr. Federico Martin Serra
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

  • microgrids
  • power electronics
  • control
  • renewable energy systems

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Related Special Issue

Published Papers (4 papers)

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Research

15 pages, 565 KiB  
Article
A Generalized Method for Rightsizing the Design of a Hybrid Microgrid
by Daniel Reich
Energies 2025, 18(7), 1643; https://doi.org/10.3390/en18071643 - 25 Mar 2025
Viewed by 192
Abstract
As the demand for sustainable and resilient energy systems grows, providing planners with effective tools for microgrid design becomes increasingly important. This research addresses the need for such tools by introducing a new method for distributed energy resource sizing in microgrid capacity planning. [...] Read more.
As the demand for sustainable and resilient energy systems grows, providing planners with effective tools for microgrid design becomes increasingly important. This research addresses the need for such tools by introducing a new method for distributed energy resource sizing in microgrid capacity planning. The planning process begins with a comprehensive assessment of the required capacity based on a given set of power load requirements. Rather than providing a single solution, as is common in related works, the sizing method introduced in this paper efficiently identifies a wide range of microgrid design options that satisfy the stated power needs. The benefit of this multi-solution approach is that it allows decision makers to consider vastly different possibilities, such as varying levels of renewables and battery storage, and weigh trade-offs between these potential designs before selecting one or more solutions for further detailed design planning. The proposed method is constructed as a three-step heuristic search procedure: (1) an exhaustive search identifies an initial set of candidate solutions; (2) a global binary search builds a diverse set of microgrid design options; and (3) a local linear search refines those options. A computational experiment is presented to demonstrate the method’s effectiveness at identifying diverse solutions sets and its computational tractability. The results show that increasing the number of capacity levels considered per distributed energy resource from 11 to 41 increases the size and diversity of the microgrid design set; however, further increasing the number of capacity levels beyond that point is not beneficial. The method presented is implemented and released in Microgrid Planner, an open source software platform. Full article
(This article belongs to the Special Issue Planning, Operation and Control of Microgrids: 2nd Edition)
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21 pages, 2291 KiB  
Article
Multi-Stage Planning Approach for Distribution Network Considering Long-Term Variations in Load and Renewable Energy
by Qihe Lou, Yanbin Li, Zhenwei Li, Liu Han, Ying Xu and Zhongkai Yi
Energies 2025, 18(1), 152; https://doi.org/10.3390/en18010152 - 2 Jan 2025
Viewed by 575
Abstract
Currently, the world is rapidly advancing in terms of the construction of new power systems, and planning suitable distribution network planning while also considering renewable energy has become a hot issue. Based on this background, this paper studies the distribution network planning problem. [...] Read more.
Currently, the world is rapidly advancing in terms of the construction of new power systems, and planning suitable distribution network planning while also considering renewable energy has become a hot issue. Based on this background, this paper studies the distribution network planning problem. Compared with the traditional planning method, the paper considers the impact of load growth and renewable energy penetration and uses the multi-stage planning method to build the planning model; at the same time, in the scenarios selection, the affinity propagation (AP) clustering algorithm is adopted, which can automatically obtain the number of clusters. Based on the proposed model, an IEEE 33-node is used for simulation. The simulation results show that, compared with the traditional static planning method, the total economic cost of the proposed method is reduced by 4.87% and the wind–solar curtailment rate is reduced by 59.01%; in addition, according to the proposed method, the impact of energy storage equipment and wind–solar permeability on the planning results is studied. It is found that, when considering energy storage, the amount of abandoned wind and light decreases by 22.35% and the total cost first decreases and then increases with the increase in wind–solar permeability, while the total economic cost reaches the minimum at about 40%. The impact of load growth rate on the planning results is also studied. Finally, the generalizability of the proposed method is investigated while using the IEEE 69-node system as an example. Full article
(This article belongs to the Special Issue Planning, Operation and Control of Microgrids: 2nd Edition)
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17 pages, 4498 KiB  
Article
Performance Evaluation of Distance Relay Operation in Distribution Systems with Integrated Distributed Energy Resources
by David R. Garibello-Narváez, Eduardo Gómez-Luna and Juan C. Vasquez
Energies 2024, 17(18), 4735; https://doi.org/10.3390/en17184735 - 23 Sep 2024
Cited by 3 | Viewed by 941
Abstract
This article presents the evaluation of the performance of the distance relay (ANSI function 21) when integrating Distributed Energy Resources (DERs) in a Local Distribution System (LDS). The aim is to understand the impacts of and the necessary modifications required in the operation [...] Read more.
This article presents the evaluation of the performance of the distance relay (ANSI function 21) when integrating Distributed Energy Resources (DERs) in a Local Distribution System (LDS). The aim is to understand the impacts of and the necessary modifications required in the operation of distance relays, considering different levels of DER aggregation, and identifying any threshold levels before issues arise. To achieve this, first, a comprehensive review was carried out to analyze the impacts generated in the protection systems. Second, by using the DigSilent Power Factory software, the implementation of the distance relay using a IEEE 13 Node Test Feeder was validated. The aggregation of the three fundamental types of DG, synchronous machines, solar panels, and wind turbines, was evaluated. The threshold at which distributed generation power injection begins to compromise distance protection performance was identified. This study compares the outcomes of using mho and quadrilateral protection schemes. Full article
(This article belongs to the Special Issue Planning, Operation and Control of Microgrids: 2nd Edition)
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16 pages, 3592 KiB  
Article
Multivariate Deep Learning Long Short-Term Memory-Based Forecasting for Microgrid Energy Management Systems
by Farid Moazzen and M. J. Hossain
Energies 2024, 17(17), 4360; https://doi.org/10.3390/en17174360 - 31 Aug 2024
Cited by 3 | Viewed by 1668
Abstract
In the scope of energy management systems (EMSs) for microgrids, the forecasting module stands out as an essential element, significantly influencing the efficacy of optimal solution policies. Forecasts for consumption, generation, and market prices play a crucial role in both day-ahead and real-time [...] Read more.
In the scope of energy management systems (EMSs) for microgrids, the forecasting module stands out as an essential element, significantly influencing the efficacy of optimal solution policies. Forecasts for consumption, generation, and market prices play a crucial role in both day-ahead and real-time decision-making processes within EMSs. This paper aims to develop a machine learning-based multivariate forecasting methodology to account for the intricate interplay pertaining to these variables from the perspective of day-ahead energy management. Specifically, our approach delves into the dynamic relationship between load demand variations and electricity price fluctuations within the microgrid EMSs. The investigation involves a comparative analysis and evaluation of recurrent neural networks’ performance to recognize the most effective technique for the forecasting module of microgrid EMSs. This study includes approaches based on Long Short-Term Memory Neural Networks (LSTMs), with architectures ranging from Vanilla LSTM, Stacked LSTM, Bi-directional LSTM, and Convolution LSTM to attention-based models. The empirical study involves analyzing real-world time-series data sourced from the Australian Energy Market (AEM), specifically focusing on historical data from the NSW state. The findings indicate that while the Triple-Stacked LSTM demonstrates superior performance for this application, it does not necessarily lead to more optimal operational costs, with forecast inaccuracies potentially causing deviations of up to forty percent from the optimal cost. Full article
(This article belongs to the Special Issue Planning, Operation and Control of Microgrids: 2nd Edition)
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