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Recent Advances in Smart Grids
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Recent Advances in Smart Grids

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

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 11966

Special Issue Editors

Dr. Majid Moazzami

E-Mail Website
Guest Editor
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Interests: power system dynamics; restructured power systems; electricity markets; renewable energy; smart grid
Dr. Hossein Shahinzadeh

E-Mail Website
Guest Editor
1. Associate Researcher, Smart Microgrid Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2. Associate Researcher, Iran Grid Secure Operation Research Institute, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Interests: microgrid; smart grids; renewable energy; energy storage; energy planning; power market
Prof. Dr. Ersan Kabalci

E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, Nevsehir Haci Bektas Veli University, Merkez/Nevşehir 50300, Turkey
Interests: power electronic applications and drives for renewable energy sources; microgrids; distributed generation; power line communication; smart grid applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Numerous nations worldwide have opted to enhance the degree of penetration of renewable energy resources (RERs) in their electricity networks due to environmental concerns, energy security issues, and concerns about fossil fuels. Aside from that, many countries have shifted toward incorporating the smart grid idea, which includes microgrids and deregulation, in their power systems to achieve reliable and secure operation, even while having a high penetration level of renewable energy resources in their power systems. In future smart grids, maintaining the operation's stability will necessitate the development of new techniques and technologies for superior control and security. As a result, the stability and security of smart grids should be thoroughly investigated and evaluated. Additionally, new protection methods are required to deal with unanticipated operational risks and contingencies. This Special Issue aims to encourage scholars to solve technical difficulties and research gaps in smart grid and microgrid systems and publish their new findings. The goal is to concentrate on the most recent developments in smart grids and microgrids, particularly in terms of operation, control, protection, security, and future concerns. Energy systems have a profound influence on daily human lives and industrial production. Various governments throughout the globe have had a transition toward restructured markets while deploying their national smart grids to take advantage of microgrids schemes and digitalized environments. Such planning programs seek long-term decarbonization and decentralization by emphasizing the importance and necessity of smart grids in their future smart cities, smart industries, and national security infrastructures, particularly by incorporating IoT-enabled infrastructures, as well as artificial intelligence models for enhancing the level of autonomy, intelligence, controllability, and observability and boosting the flexibility in various layers of power systems. However, at the same time, it is impossible to ignore the practical challenges associated with the operation, control, protection, and security of present and future smart grids. As a result, this Special Issue will attempt to cover research gaps in the smart grid domain while also motivating researchers on novel topics that greatly impact social welfare.

Dr. Majid Moazzami
Dr. Hossein Shahinzadeh
Prof. Dr. Ersan Kabalci
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

  • smart grids and microgrids
  • the design, modeling, control, and management of smart grids and microgrids
  • smart grid and microgrid reliability, sustainability, flexibility, protection, security, and resiliency
  • intelligent systems, solving methods, optimization, and advanced heuristics for smart grids and microgrids
  • the modeling, planning, and operating of renewable energy resources in modern power systems
  • business models for different electricity market players in smart grids and microgrids
  • demand-side management and demand response
  • optimal sizing, placement, and operation of energy storage systems and electric vehicles in smart grids
  • smart homes and building energy management
  • electricity market, electrical power, and energy systems
  • IoT for the concept of smart grids and microgrids

Published Papers (7 papers)

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Research

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19 pages, 10944 KiB  
Article
Data-Driven Management Systems for Wave-Powered Renewable Energy Communities
by Saqib Iqbal and Kamyar Mehran
Energies 2024, 17(5), 1197; https://doi.org/10.3390/en17051197 - 2 Mar 2024
Viewed by 462
Abstract
This research focus on the essential task of precise prediction for power generation and energy consumption of wave energy converters (WECs) within the framework of contemporary wave-powered renewable energy sources (RESs). Utilizing real-time wave data, we introduce a deep learning methodology featuring a [...] Read more.
This research focus on the essential task of precise prediction for power generation and energy consumption of wave energy converters (WECs) within the framework of contemporary wave-powered renewable energy sources (RESs). Utilizing real-time wave data, we introduce a deep learning methodology featuring a long short-term memory (LSTM) model. Additionally, we propose an online management system for RESs aimed at optimizing interactions among WECs, energy storage systems (ESSs), super capacitor (SC), and load. This approach leads to significant enhancements in mean square error (MSE) for critical variables such as wave height, time period, and direction, improving predictive accuracy by factors of 8.37, 9.30, and 16.14, respectively. Through diverse scenario-based experimental evaluations, our solution exhibits competitive performance when compared to benchmark strategies and ideal solutions. These findings underscore the potential of the LSTM-NN model to advance the efficiency and reliability of wave energy forecasting and management systems. As wave energy technology evolves, this study contributes to ongoing efforts to enhance practical applicability, especially in coastal regions with substantial wave energy potential. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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19 pages, 3312 KiB  
Article
Few-Shot Metering Anomaly Diagnosis with Variable Relation Mining
by Jianqiao Sun, Wei Zhang, Peng Guo, Xunan Ding, Chaohui Wang and Fei Wang
Energies 2024, 17(5), 993; https://doi.org/10.3390/en17050993 - 20 Feb 2024
Viewed by 500
Abstract
Metering anomalies not only mean huge economic losses but also indicate the faults of equipment and power lines, especially within the substation. As a result, metering anomaly diagnosis is becoming one of the most important missions in smart grids. However, due to the [...] Read more.
Metering anomalies not only mean huge economic losses but also indicate the faults of equipment and power lines, especially within the substation. As a result, metering anomaly diagnosis is becoming one of the most important missions in smart grids. However, due to the insufficient and imbalanced anomaly cases, identifying the anomalies in smart meter data accurately and efficiently remains challenging. Existing methods usually employ few-shot learning models in computer vision directly, which requires the rich experience of human experts and sufficient abnormal cases for training. It blocks model generalizing to various application scenarios. To address these shortcomings, we propose a novel framework for metering anomaly diagnosis based on few-shot learning, named FSMAD. Firstly, we design a fault data injection model to emulate anomalies, so that no abnormal samples are required in the training phase. Secondly, we provide a learnable variable transformation to reveal inherent relationships among various smart meter data and help FSMAD extract more efficient features. Finally, the deeper metric network is equipped to support FSMAD in obtaining powerful comparison capability. Extensive experiments on a real-world dataset demonstrate the advantages of our FSMAD over state-of-the-art methods. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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23 pages, 2661 KiB  
Article
Efficient Microgrid Management with Meerkat Optimization for Energy Storage, Renewables, Hydrogen Storage, Demand Response, and EV Charging
by Hossein Jokar, Taher Niknam, Moslem Dehghani, Ehsan Sheybani, Motahareh Pourbehzadi and Giti Javidi
Energies 2024, 17(1), 25; https://doi.org/10.3390/en17010025 - 20 Dec 2023
Viewed by 958
Abstract
Within microgrids (MGs), the integration of renewable energy resources (RERs), plug-in hybrid electric vehicles (PHEVs), combined heat and power (CHP) systems, demand response (DR) initiatives, and energy storage solutions poses intricate scheduling challenges. Coordinating these diverse components is pivotal for optimizing MG performance. [...] Read more.
Within microgrids (MGs), the integration of renewable energy resources (RERs), plug-in hybrid electric vehicles (PHEVs), combined heat and power (CHP) systems, demand response (DR) initiatives, and energy storage solutions poses intricate scheduling challenges. Coordinating these diverse components is pivotal for optimizing MG performance. This study presents an innovative stochastic framework to streamline energy management in MGs, covering proton exchange membrane fuel cell–CHP (PEMFC-CHP) units, RERs, PHEVs, and various storage methods. To tackle uncertainties in PHEV and RER models, we employ the robust Monte Carlo Simulation (MCS) technique. Challenges related to hydrogen storage strategies in PEMFC-CHP units are addressed through a customized mixed-integer nonlinear programming (MINLP) approach. The integration of intelligent charging protocols governing PHEV charging dynamics is emphasized. Our primary goal centers on maximizing market profits, serving as the foundation for our optimization endeavors. At the heart of our approach is the Meerkat Optimization Algorithm (MOA), unraveling optimal MG operation amidst the intermittent nature of uncertain parameters. To amplify its exploratory capabilities and expedite global optima discovery, we enhance the MOA algorithm. The revised summary commences by outlining the overall goal and core algorithm, followed by a detailed explanation of optimization points for each MG component. Rigorous validation is executed using a conventional test system across diverse planning horizons. A comprehensive comparative analysis spanning varied scenarios establishes our proposed method as a benchmark against existing alternatives. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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18 pages, 4187 KiB  
Article
Optimal Protection Coordination of Active Distribution Networks Using Smart Selection of Short Circuit Voltage-Based Relay Characteristics
by Ali Vafadar, Maryam A. Hejazi, Hamed Hashemi-Dezaki and Negin Mohagheghi
Energies 2023, 16(14), 5301; https://doi.org/10.3390/en16145301 - 11 Jul 2023
Cited by 1 | Viewed by 1290
Abstract
Much attention has been paid to the optimized protection of microgrids (MGs) and active distribution networks (ADNs). However, the literature shows a research gap in proposing a hybrid scheme, utilizing the voltage-based and overcurrent-based relays, while the voltage relay characteristics are smartly selected. [...] Read more.
Much attention has been paid to the optimized protection of microgrids (MGs) and active distribution networks (ADNs). However, the literature shows a research gap in proposing a hybrid scheme, utilizing the voltage-based and overcurrent-based relays, while the voltage relay characteristics are smartly selected. This study aims to address such a research gap. This article presents an optimal hybrid protection coordination method for ADNs and MGs. Considering that any system fault is associated with a voltage drop, a new protection method is formulated from voltage analysis under fault conditions. The proposed method is independent of the type, size, and location of distributed generation (DG) units, as well as the operation of the distribution system connected to the grid. This method uses only the local voltage to determine the relay’s tripping time and is a low-cost protection method, in addition to the directional overcurrent relays (DOCRs). Optimizing the voltage-based relay characteristics is one of the most important contributions, which leads to improving the protection system speed and its selectivity concerns. The effectiveness of the proposed method has been verified by several simulation tests performed on the medium voltage (MV) distribution system under different fault conditions and DG size and location. The simulation results show that the protection method has appropriate speed, and the protection settings could be independent of the operation modes/topologies and the locations of faults. The comparative results illustrate the advantages of the proposed hybrid protective scheme. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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17 pages, 8225 KiB  
Article
Long-Term Electricity Demand Forecasting in the Steel Complex Micro-Grid Electricity Supply Chain—A Coupled Approach
by Sepehr Moalem, Roya M. Ahari, Ghazanfar Shahgholian, Majid Moazzami and Seyed Mohammad Kazemi
Energies 2022, 15(21), 7972; https://doi.org/10.3390/en15217972 - 27 Oct 2022
Cited by 4 | Viewed by 1502
Abstract
Demand forecasting produces valuable information for optimal supply chain management. The basic metals industry is the most energy-intensive industries in the electricity supply chain. There are some differences between this chain and other supply chains including the impossibility of large-scale energy storage, reservation [...] Read more.
Demand forecasting produces valuable information for optimal supply chain management. The basic metals industry is the most energy-intensive industries in the electricity supply chain. There are some differences between this chain and other supply chains including the impossibility of large-scale energy storage, reservation constraints, high costs, limitations on electricity transmission lines capacity, real-time response to high-priority strategic demand, and a variety of energy rates at different hours and seasons. A coupled demand forecasting approach is presented in this paper to forecast the demand time series of the metal industries microgrid with minimum available input data (only demand time series). The proposed method consists of wavelet decomposition in the first step. The training subsets and the validation subsets are used in the training and fine-tuning of the LSTM model using the ELATLBO method. The ESC dataset used in this study for electrical demand forecasting includes 24-h daily over 40 months from 21 March 2017, to 21 June 2020. The obtained results have been compared with the results of Support Vector Machine (SVM), Decision Tree, Boosted Tree, and Random Forest forecasting models optimized using the Bayesian Optimization (BO) method. The results show that performance of the proposed method is well in demand forecasting of the metal industries. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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22 pages, 1134 KiB  
Article
Frequency Stabilization of AC Microgrid Clusters: An Efficient Fractional Order Supercapacitor Controller Approach
by Md. Shafiul Alam, Abdullah A. Almehizia, Fahad Saleh Al-Ismail, Md. Alamgir Hossain, Muhammad Azharul Islam, Md. Shafiullah and Aasim Ullah
Energies 2022, 15(14), 5179; https://doi.org/10.3390/en15145179 - 17 Jul 2022
Cited by 9 | Viewed by 2081
Abstract
An autonomous microgrid is often formed by incorporating distributed generators into the distribution system. However, distributed generators have less inertia compared to traditional synchronous generators, and can cause the system frequency to become unstable. Additionally, as more clusters are integrated into the distribution [...] Read more.
An autonomous microgrid is often formed by incorporating distributed generators into the distribution system. However, distributed generators have less inertia compared to traditional synchronous generators, and can cause the system frequency to become unstable. Additionally, as more clusters are integrated into the distribution microgrid, frequency instability increases. To resolve frequency instability in the microgrid cluster, this study proposes a supercapacitor control approach. The microgrid consists of several clusters which integrate wind power generators, solar PV, STP, fuel cells, aqua electrolyzers, and diesel generators. Initially, a small signal model is developed to facilitate the control design. A fractional-order supercapacitor controller is augmented with the developed small-signal model to stabilize the frequency of the microgrid. Furthermore, the controller parameters are optimized to guarantee robust controller performance. The proposed fractional-order supercapacitor controller provides more degrees of freedom compared to the conventional controller. Time-domain simulations were carried out considering several real-time scenarios to test the performance of the proposed controller. We observed that the presented approach is capable of stabilizing the system frequency in all cases. Furthermore, the proposed approach outperforms existing approaches in stabilizing the frequency of the microgrid cluster. Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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Review

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22 pages, 5343 KiB  
Review
Wind Energy Conversion Systems Based on a Synchronous Generator: Comparative Review of Control Methods and Performance
by Amir Raouf, Kotb B. Tawfiq, Elsayed Tag Eldin, Hossam Youssef and Elwy E. El-Kholy
Energies 2023, 16(5), 2147; https://doi.org/10.3390/en16052147 - 22 Feb 2023
Cited by 8 | Viewed by 3952
Abstract
Recently, controlling a wind energy conversion system (WECS) under fluctuating wind speed and enhancing the quality of power delivered to the grid has been a demanding challenge for many researchers. This paper provides a comprehensive review of synchronous generator-based WECSs. This paper will [...] Read more.
Recently, controlling a wind energy conversion system (WECS) under fluctuating wind speed and enhancing the quality of power delivered to the grid has been a demanding challenge for many researchers. This paper provides a comprehensive review of synchronous generator-based WECSs. This paper will investigate the growth of wind energy in Egypt and throughout the world, as well as the technological and financial significance of wind energy. The block diagram of a typical grid-connected WECS, power control techniques, characteristic power curve-based maximum power point tracking (MPPT), and MPPT techniques are also presented in this study. Moreover, this study compares different power converter topologies for grid-connected and independent WECSs that use a permanent magnet synchronous generator (PMSG). Full article
(This article belongs to the Special Issue Recent Advances in Smart Grids)
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