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Application of AI, IoT, and Blockchain in Smart Grids with Distributed Energy Resources

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (15 October 2022) | Viewed by 12968

Special Issue Editors


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Guest Editor
College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
Interests: electricity market; intelligent control; load frequency control; planning and operation; renewable energy; smart grid and microgrids
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Science and Engineering, Flinders University, Adelaide 5042, Australia
Interests: electrical machines and energy conversion; power electronics and electrical drives; renewable energy systems and energy storage; electric vehicles; power system analysis distributed generation
Special Issues, Collections and Topics in MDPI journals
Department of Electrical and Computer Engineering, the University of New Mexico, Albuquerque, NM 87131, United States
Interests: power system protection; microgrids; grid integration of renwable energy resources
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Interests: reliability and security of the power systems; energy management systems; microgrids; smart grids; planning and operation of renewable resources; electric vehicles and storage systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
SREM, University of South Australia, Adelaide 5042, Australia
Interests: electrical machines and drives; hybrid power networks; renewable energy systems; transmission and distribution networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last decade, the smart grid concept has become well known for the digitalization of the energy sector. A smart grid is an energy network/grid enabling a two-way flow of energy and data. It represents an unprecedented opportunity to move the energy industry into a new era of efficiency, availability, and reliability that will contribute to solving both environmental and economic issues. Smart grid has facilitated the integration of distributed energy resources (DERs) into power systems. In addition, the demand response has been used under the smart grid concept. However, communication between all the available components in smart grids is a major challenge. Hence, big data analysis and the internet of things (IoT) are more important than ever before for the development of smart grids.

Artificial intelligence (AI) is an important technology driver for smart grids. AI techniques have attracted much attention for data analysis and decision making in smart grids. The outstanding features of these techniques make them a powerful tool for solving complex engineering problems with large state spaces. AI can provide unique solutions for power grid balance, energy consumption analysis, and energy production. AI techniques enable decision making with speed and accuracy. To this end, they use massive amounts of data to create intelligent algorithms that can handle tasks requiring human intelligence. The most common methods for achieving AI systems are fuzzy logic, expert systems, neural networks, and natural language processing.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • AI for transactive energy
  • Energy management by blockchain in smart grids
  • Planning and operation of smart grids
  • Demand response for increasing the penetration level of DERs
  • AI for optimization of smart grids
  • Internet of things in smart grids operation
  • AI for peer-to-peer energy sharing
  • Intelligent control of microgrids
  • Resiliency, reliability, and security enhancement of smart grids
  • AI for energy demand and generation forecasting in the power market
  • AI for battery lifetime estimation in smart grids
  • Smart grid flexibility improvement by AI
  • AI application for electric vehicle integration in smart grid
  • AI for integration of distributed energy resources

Dr. Rahmat Khezri
Dr. Amin Mahmoudi
Dr. Ali Bidram
Dr. Mostafa Shaaban
Dr. Solmaz Kahourzade
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. Sustainability 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 2400 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

  • artificial intelligence
  • blockchain
  • charging station
  • distributed energy resources
  • electric vehicle
  • electricity market
  • energy forecasting
  • energy sharing
  • energy storage system
  • internet of things
  • imtelligent control
  • machine learning
  • microgrids
  • multi-energy network
  • planning and operation
  • renewable energy
  • smart grid
  • sustainability
  • wind turbine

Published Papers (6 papers)

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Research

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15 pages, 3511 KiB  
Article
Replay-Attack Detection and Prevention Mechanism in Industry 4.0 Landscape for Secure SECS/GEM Communications
by Mahmood A. Al-Shareeda, Selvakumar Manickam, Shams A. Laghari and Ashish Jaisan
Sustainability 2022, 14(23), 15900; https://doi.org/10.3390/su142315900 - 29 Nov 2022
Cited by 22 | Viewed by 3731
Abstract
Starting from the First Industrial Revolution to the current and Fourth Industrial Revolution (or Industry 4.0), various industrial machines are present in the market and manufacturing companies. As standardized protocols have become increasingly popular, more utilities are switching to Internet Protocol (IP)-based systems [...] Read more.
Starting from the First Industrial Revolution to the current and Fourth Industrial Revolution (or Industry 4.0), various industrial machines are present in the market and manufacturing companies. As standardized protocols have become increasingly popular, more utilities are switching to Internet Protocol (IP)-based systems for wide-area communication. SECS/GEM is one of the standards that permit industries to collect information directly from the machines, either using RS323 or TCP/IP communication. TCP/IP communication is becoming more critical than ever, especially given our accelerated digital transformation and increasing reliance on communication technologies. The growth of IT is accelerating with cyberthreats as well. In contrast, security features in the SECS/GEM protocol may be neglected by some companies as it is only used in factories and not mostly used in the outside world. However, communication of SECS/GEM is highly susceptible to various cyberattacks. This paper analyzes the potential replay-attack cyberattacks that can occur on a SECS/GEM system. In replay attacks, this paper supposes an adversary that wants to damage an operation-based control system in an ongoing condition. The adversary has the ability to capture messages to watch and record their contents for a predetermined amount of time, record them, and then replay them while attacking in order to inject an exogenous control input undetected. The paper’s objectives are to prove that SECS/GEM communication is vulnerable to cyberattack and design a detection mechanism to protect SECS/GEM communications from replay attacks. The methodology implements a simulation of the replay-attack mechanism on SECS/GEM communication. The results indicate that the design mechanism detected replay attacks against SECS/GEM communications and successfully prevented them. Full article
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21 pages, 656 KiB  
Article
Optimal Operational Planning of RES and HESS in Smart Grids Considering Demand Response and DSTATCOM Functionality of the Interfacing Inverters
by Abdelfatah Ali, Mostafa F. Shaaban and Hatem F. Sindi
Sustainability 2022, 14(20), 13209; https://doi.org/10.3390/su142013209 - 14 Oct 2022
Cited by 2 | Viewed by 1006
Abstract
With countries moving toward renewable energy sources (RES), the need for dispatchability and storage solutions has become more prevalent. The uncertainty associated with wind turbine (WT) units and photovoltaic (PV) systems further complex a system with a high level of intermittency. This work [...] Read more.
With countries moving toward renewable energy sources (RES), the need for dispatchability and storage solutions has become more prevalent. The uncertainty associated with wind turbine (WT) units and photovoltaic (PV) systems further complex a system with a high level of intermittency. This work addresses this problem by proposing an operational planning approach to determine the optimal allocation of WT units, PV systems, and hybrid energy storage systems (HESS) in smart grids. The proposed approach considers the uncertainties of the RES and load demand, price-based demand response, and distribution static compensator (DSTATCOM) functionality of the RES interfacing inverters. The operational planning problem is divided into two subcategories: (1) optimal long-term planning and (2) optimal operation. In the first problem, probabilistic models of RES and load reflect on the sizes and locations of the used RES and storage technologies. This allocation is further optimized via the optimal operation of the smart grid. The proposed operational planning approach is formulated as a nested optimization problem that guarantees the optimal planning and operation of the RES and HESS simultaneously. This approach is tested on the IEEE 33-bus distribution system and solved using meta-heuristic and mathematical algorithms. The effectiveness of the proposed approach is demonstrated using a set of case studies. The results demonstrate that the proposed approach optimally allocates the RES and HESS with a 30.4% cost reduction and 19% voltage profile improvement. Full article
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20 pages, 1224 KiB  
Article
Blockchain and IoT-Driven Optimized Consensus Mechanism for Electric Vehicle Scheduling at Charging Stations
by Riya Kakkar, Rajesh Gupta, Smita Agrawal, Sudeep Tanwar, Ahmed Altameem, Torki Altameem, Ravi Sharma, Florin-Emilian Turcanu and Maria Simona Raboaca
Sustainability 2022, 14(19), 12800; https://doi.org/10.3390/su141912800 - 07 Oct 2022
Cited by 9 | Viewed by 2032
Abstract
The emerging demand for electric vehicles in urban cities leads to the need to install a huge number of charging stations. With this requirement, electric vehicle coordination and scheduling at charging stations in real-time becomes highly tedious. Thus, there is a need for [...] Read more.
The emerging demand for electric vehicles in urban cities leads to the need to install a huge number of charging stations. With this requirement, electric vehicle coordination and scheduling at charging stations in real-time becomes highly tedious. Thus, there is a need for an efficient scheduling mechanism for electric vehicle charging at charging stations. This paper proposes a novel blockchain and Internet of Things-based consensus mechanism called COME for secure and trustable electric vehicle scheduling at charging stations. The proposed mechanism is intending to resolve conflicts at charging stations. The integrated InterPlanetary File System protocol facilitates a cost-efficient mechanism with minimized bandwidth for electric vehicle scheduling. The proposed mechanism ensures that there is no loss for either the electric vehicle or the charging station. We formulate different scenarios for electric vehicle charging and apply different scheduling algorithms, including first-come first-served, longest remaining time first, and coalition game theory. The performance of the proposed COME consensus mechanism is estimated by comparing it with the practical Byzantine Fault Tolerance consensus protocol and traditional systems based on the charging demand, wait time, conflict resolution, scalability, and InterPlanetary File System bandwidth parameters. The performance results show that the proposed COME consensus mechanism ensures that electric vehicles can have their vehicle charged without any conflict and that the charging station can be satisfied in terms of profit. Moreover, the proposed COME consensus mechanism outperforms the both practical Byzantine Fault Tolerance consensus protocol and the traditional system in terms of scalability and conflict resolution along with additional parameters such as wait time, charging demand, and bandwidth analysis. Full article
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14 pages, 1185 KiB  
Article
A New Cooperative Game—Theoretic Approach for Customer-Owned Energy Storage
by Maria O. Hanna, Mostafa F. Shaaban and Magdy M. A. Salama
Sustainability 2022, 14(6), 3676; https://doi.org/10.3390/su14063676 - 21 Mar 2022
Viewed by 1533
Abstract
The increasing demand for energy storage systems (ESSs) alongside the continuous enhancements to storage technology have been of great positive impact on the electric grid. Their unceasing development has been driven by the need to accommodate increased penetration of renewable energy resources and [...] Read more.
The increasing demand for energy storage systems (ESSs) alongside the continuous enhancements to storage technology have been of great positive impact on the electric grid. Their unceasing development has been driven by the need to accommodate increased penetration of renewable energy resources and defer capital investments, among other benefits. Moreover, ESSs have played a key role in the grid’s ability to cope with its ever-shifting load profiles, resulting in large economic gain for ESS owners. For this reason, this prospective study was designed to investigate privately-owned energy storage hubs (ESHs) and their interactions with potential customers as well as with the electric grid. This research examined two contrasting interaction approaches for customer-owned stationary energy storage hubs: a cooperative and a non-cooperative game-theoretic approach. The goal of the cooperative technique is to conduce to a correlated equilibrium increasing the social welfare of all players involved using a regret matching algorithm. On the other hand, in the non-cooperative approach, modeled as an ascending price-clinching auction, each player acts greedily, maximizing only their individual welfare. Implementing both case studies resulted in important insights into ESH players’ interactions and provided contrasting methods of modeling their behaviors. Finally, depending on the application at hand, the choice of one approach may be more realistic than the other. Full article
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25 pages, 6461 KiB  
Article
Optimal Planning of Remote Microgrids with Multi-Size Split-Diesel Generators
by Gabriel Andres Rojas Cardenas, Rahmat Khezri, Amin Mahmoudi and Solmaz Kahourzadeh
Sustainability 2022, 14(5), 2892; https://doi.org/10.3390/su14052892 - 02 Mar 2022
Cited by 9 | Viewed by 1706
Abstract
This paper proposes a multi-size Split-diesel generator (Split-DG) model with three different sizes of DGs and more switching configurations compared to the existing split-DG models. The proposed multi-size Split-DG system is examined for optimal sizing of remote microgrids with and without renewable-battery system. [...] Read more.
This paper proposes a multi-size Split-diesel generator (Split-DG) model with three different sizes of DGs and more switching configurations compared to the existing split-DG models. The proposed multi-size Split-DG system is examined for optimal sizing of remote microgrids with and without renewable-battery system. As a novel concept, multi-size Split-DG is used to reduce contamination, cost, and dumped power by using multiple small DGs to replace the single-size large DG. As another contribution of this study, a practical model is developed by considering the capacity degradation of components, spinning reserve, as well as DG’s and fuel tank’s constraints. The optimization problem is solved using a variable weighting particle swarm optimization (VW-PSO) algorithm. The effectiveness of the proposed Split-DG systems, optimized by the developed VW-PSO, is verified by comparing the results with conventional single-size DG system and the system optimized by conventional PSO. While the formulated optimization problem is general and can be used for any remote microgrids, an aboriginal community in South Australia is examined in this study. For this purpose, realistic data of load and weather, as well as technical and economic data of components, are used. It is found that the Split-DG-PV-WT-BES system has the lowest electricity cost compared to the systems without BES, or without PV and WT. Full article
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Review

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18 pages, 1717 KiB  
Review
An Exploratory Study of the Perception of Peer-to-Peer Energy Trading within the Power Distribution Network in the UAE
by Ahmed Hassan Almarzooqi, Ahmed H. Osman, Mostafa Shabaan and Mohammed Nassar
Sustainability 2023, 15(6), 4891; https://doi.org/10.3390/su15064891 - 09 Mar 2023
Cited by 3 | Viewed by 1655
Abstract
The introduction of Smart Grid resulted in the development of various applications that are built upon the concept of bi-directional flow of electricity and data. One of the Smart Grids pillars is the Distributed Generation (DG) technologies, where customers turn to be prosumers [...] Read more.
The introduction of Smart Grid resulted in the development of various applications that are built upon the concept of bi-directional flow of electricity and data. One of the Smart Grids pillars is the Distributed Generation (DG) technologies, where customers turn to be prosumers with power generation capability. Another pillar is the Demand Side Management (DSM), which helps control the energy consumption by changing the power usage slots among other peers. DG and DSM have facilitated the sharing of excess power by customers to the grid, and then to their peers through the grid as a trading agent. Although the concept of integrating Peer-to-Peer energy trading with DSM has been explored by scholars and relatively established trading frameworks, there are very limited research performed in respect to the UAE market in terms of its acceptance and readiness towards this energy trading market. This research aims to explore the perception of Peer-to-Peer electricity trading within the Power Distribution Network in the United Arab Emirates. The study will review the Smart Grid network in the UAE and will obtain insights on people’s perception of the transition from classical electricity network to Smart Grid. It will also look into peoples’ perception regarding the transition from being electricity consumers to being electricity producers that trade among peers through semi-structured interviews. This will enhance the understanding of the energy trading market between self-generated power producers connected to a network grid, where the consumer will be utilizing the excess power available in the form of electricity trading, by importing and exporting power, without adding any additional power to the grid. The outcome of the study will provide an insight on the UAE electricity market by designing an electricity trading model that is built upon the following vital factors: power quality, supply reliability, type of integration, peers, and trading time. Furthermore, the study will provide a foundation base to the utilities, as well as individuals, when dealing with the changes in the electricity market structure. Full article
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