Special Issue "Applications of IoT for Microgrids"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Dr. Shama Islam
Website
Guest Editor
School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia
Interests: energy management; demand response; peer-to-peer energy trading; smart grid communication; energy storage systems; data analytics for smart grid; IoT for smart energy systems
Dr. Apel Mahmud
Website
Guest Editor
Center for Smart Power and Energy Research, School of Engineering, Deakin University, Geelong, VIC 3216, Australia
Interests: power system modelling; power system stability and control; microgrids (AC, DC, and hybrid AC/DC); grid integration of renewable energy sources (small- and large-scale); transactive energy management and optimization for microgrids; nonlinear control theory and applications
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of small-scale solar photovoltaic (PV) and battery energy storage systems (BESSs) has created the opportunity to operate energy systems in a different way. These solar PV and BESSs can be grouped together to supply power in a small area in the form of microgrids, where multiple microgrids can be connected together. The advancement of information and communication technologies has enabled ubiquitous communication among different devices, along with the integration of advanced computing and decision-making features. Incorporating IoT applications in a microgrid allows useful insights into energy consumption and generation patterns, new opportunities for energy trading, as well as innovative strategies for power sharing. This Special Issue focuses on different IoT applications for microgrids and will stress, among others, on the following main topics:

  • IoT for local energy trading in microgrids
  • Energy management in microgrids
  • Modeling of local energy markets in microgrids
  • Power sharing strategies for both individual and multiple microgrids
  • Information and communication infrastructure for IoT enabled local energy trading
  • Open energy-sharing platforms
  • Cyber security for IoT-enabled local energy trading
  • Applications of IoT for power conversions in microgrids

The Special Issue solicits original theoretical and practical contributions, including review papers, on any relevant area of IoT applications for microgrid. We would like to cordially invite you to contribute to this Special Issue. 

Dr. Shama Islam
Dr. Apel Mahmud
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 papers will be 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. Electronics is an international peer-reviewed open access monthly 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 1500 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

  • IoT for microgrids
  • Local energy trading
  • Peer-to-peer energy trading
  • Game theoretic approach for energy trading
  • Energy sharing
  • Transactive energy market
  • Open energy-sharing platform
  • Energy hub
  • Communication infrastructure for energy trading
  • Energy management

Published Papers (6 papers)

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Research

Open AccessArticle
Development of Cluster-Based Energy Management Scheme for Residential Usages in the Smart Grid Community
Electronics 2020, 9(9), 1462; https://doi.org/10.3390/electronics9091462 - 07 Sep 2020
Abstract
Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy [...] Read more.
Several efforts have been taken to promote clean energy towards a sustainable and green economy. Existing sources of electricity present some complications concerning consumers, utility owners, and the environment. Utility operators encourage household applicants to employ residential energy management (REM) systems. Renewable energy sources (RESs), energy storage systems (ESS), and optimal energy allocation strategies are used to resolve these difficulties. In this paper, the development of a cluster-based energy management scheme for residential consumers of a smart grid community is proposed to reduce energy use and monetary cost. Normally, residential consumers deal with household appliances with various operating time slots depending on consumer preferences. A simulator is designed and developed using C++ software to resolve the residential consumer’s REM problem. The benefits of the RESs, ESS, and optimal energy allocation techniques are analyzed by taking in account three different scenarios. Extensive case studies are carried out to validate the effectiveness of the proposed cluster-based energy management scheme. It is demonstrated that the proposed method can save energy and costs up to 45% and 56% compared to the existing methods. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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Open AccessFeature PaperArticle
GridAttackSim: A Cyber Attack Simulation Framework for Smart Grids
Electronics 2020, 9(8), 1218; https://doi.org/10.3390/electronics9081218 - 29 Jul 2020
Abstract
The smart grid system is one of the key infrastructures required to sustain our future society. It is a complex system that comprises two independent parts: power grids and communication networks. There have been several cyber attacks on smart grid systems in recent [...] Read more.
The smart grid system is one of the key infrastructures required to sustain our future society. It is a complex system that comprises two independent parts: power grids and communication networks. There have been several cyber attacks on smart grid systems in recent years that have caused significant consequences. Therefore, cybersecurity training specific to the smart grid system is essential in order to handle these security issues adequately. Unfortunately, concepts related to automation, ICT, smart grids, and other physical sectors are typically not covered by conventional training and education methods. These cybersecurity experiences can be achieved by conducting training using a smart grid co-simulation, which is the integration of at least two simulation models. However, there has been little effort to research attack simulation tools for smart grids. In this research, we first review the existing research in the field, and then propose a smart grid attack co-simulation framework called GridAttackSim based on the combination of GridLAB-D, ns-3, and FNCS. The proposed architecture allows us to simulate smart grid infrastructure features with various cybersecurity attacks and then visualize their consequences automatically. Furthermore, the simulator not only features a set of built-in attack profiles but also enables scientists and electric utilities interested in improving smart grid security to design new ones. Case studies were conducted to validate the key functionalities of the proposed framework. The simulation results are supported by relevant works in the field, and the system can potentially be deployed for cybersecurity training and research. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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Open AccessArticle
Efficient Electricity Management System for Optimal Peak/Off-Peak Hour Pricing
Electronics 2020, 9(8), 1189; https://doi.org/10.3390/electronics9081189 - 24 Jul 2020
Abstract
With the advent of new technologies and an alarming increase in the world’s population, there has been a rapid increase in energy consumption. Consequently, this has resulted in a surge in developing sources that generate electricity and concurrently escalating global warming levels. Owing [...] Read more.
With the advent of new technologies and an alarming increase in the world’s population, there has been a rapid increase in energy consumption. Consequently, this has resulted in a surge in developing sources that generate electricity and concurrently escalating global warming levels. Owing to their contributions in vast applications, dependence on renewable energy is a reliable option. However, it is known that a complete and efficient utilization of the incoming solar radiation is not feasible, taking into account the various losses associated. Our proposal addresses concerns resulting in the efficient utilization of solar energy based on optimal cost analysis by the mathematical procedure. This methodology when used along with a battery-based photovoltaic (PV) system effectively reduces the amount of electricity imported from the grid. The implementation of this method scales down the monthly electricity consumption by 67.1%. Our findings were established considering South Korea’s residential electricity tariff system. Our system works based on a principle where the batteries are charged with solar PV during off-peak hours and discharged during peak hours. The state of charge of the battery could be monitored using a web server. In situations, wherein the load demand cannot be sustained by the batteries, grid power can be utilized during peak hours. The sequence of these events can be implemented by a series of algorithms. Our proposed system also helps in achieving the goal-7 of the sustainable development goals (SDG) prescribed by the United Nations (UN), which is to boost the consumption of renewable energy which ultimately results in monetary savings to a large extent. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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Open AccessFeature PaperArticle
Machine Learning to Ensure Data Integrity in Power System Topological Network Database
Electronics 2020, 9(4), 693; https://doi.org/10.3390/electronics9040693 - 24 Apr 2020
Cited by 1
Abstract
Operational and planning modules of energy systems heavily depend on the information of the underlying topological and electric parameters, which are often kept in database within the operation centre. Therefore, these operational and planning modules are vulnerable to cyber anomalies due to accidental [...] Read more.
Operational and planning modules of energy systems heavily depend on the information of the underlying topological and electric parameters, which are often kept in database within the operation centre. Therefore, these operational and planning modules are vulnerable to cyber anomalies due to accidental or deliberate changes in the power system database model. To validate, we have demonstrated the impact of cyber-anomalies on the database model used for operation of energy systems. To counter these cyber-anomalies, we have proposed a defence mechanism based on widely accepted classification techniques to identify the abnormal class of anomalies. In this study, we find that our proposed method based on multilayer perceptron (MLP), which is a special class of feedforward artificial neural network (ANN), outperforms other exiting techniques. The proposed method is validated using IEEE 33-bus and 24-bus reliability test system and analysed using ten different datasets to show the effectiveness of the proposed method in securing the Optimal Power Flow (OPF) module against data integrity anomalies. This paper highlights that the proposed machine learning-based anomaly detection technique successfully identifies the energy database manipulation at a high detection rate allowing only few false alarms. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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Open AccessFeature PaperArticle
Development of a Prototype for Monitoring Photovoltaic Self-Consumption Systems
Electronics 2020, 9(1), 67; https://doi.org/10.3390/electronics9010067 - 01 Jan 2020
Abstract
Currently, the increasing energy consumption around the world and the environmental impact resulting from the use of fossil fuel-based energy have promoted the use of renewable energy sources such as photovoltaic solar energy. The main characteristic of this type of energy is its [...] Read more.
Currently, the increasing energy consumption around the world and the environmental impact resulting from the use of fossil fuel-based energy have promoted the use of renewable energy sources such as photovoltaic solar energy. The main characteristic of this type of energy is its unpredictability, as it depends on meteorological conditions. In this sense, monitoring the power generation of photovoltaic systems (PVS) in order to analyze their performance is becoming crucial. The purpose of this paper is to design a monitoring system for a residential photovoltaic self-consumption system which employs an Internet of Things (IoT) platform to estimate the photovoltaic power generation according to solar radiation and temperature. The architecture of the developed prototype will be described and the benefits of providing the use of IoT for monitoring will be highlighted, since all data collected by the data acquisition system (DAS) may be stored in the Cloud. The comparison of the results with those of other monitoring systems was very positive, with an uncertainty that complies with the IEC61724 standard. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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Open AccessFeature PaperArticle
A New Pricing Scheme for Intra-Microgrid and Inter-Microgrid Local Energy Trading
Electronics 2019, 8(8), 898; https://doi.org/10.3390/electronics8080898 - 14 Aug 2019
Cited by 4
Abstract
In this paper, an optimum pricing scheme has been designed to maximize the profits earned by sellers in microgrids through intra-microgrid and inter-microgrid local energy trading. The pricing function is optimized for different priority groups of participants within the microgrid and it is [...] Read more.
In this paper, an optimum pricing scheme has been designed to maximize the profits earned by sellers in microgrids through intra-microgrid and inter-microgrid local energy trading. The pricing function is optimized for different priority groups of participants within the microgrid and it is represented as a linear function of the energy sold/purchased during energy trading. A non-linear optimization problem has been formulated to optimize the amount of energy sold, as well as the coefficients of pricing function with an objective to maximize the profit for the sellers at a certain time instant. The numerical simulation results demonstrate that the proposed approach can reduce energy mismatch at the participants compared to the case when different priority groups are not considered. The findings also illustrate that the optimum pricing function can achieve higher profit for the sellers when compared with existing pricing schemes. Full article
(This article belongs to the Special Issue Applications of IoT for Microgrids)
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