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Smart Grid Control and Optimization (Volume II)

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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 (3 November 2023) | Viewed by 4230

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Special Issue Editor

Prof. Dr. David Dorrell

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Guest Editor

School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg 2000, South Africa
Interests: electric machines; motors; renewable energy; power systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As traditional grid systems transition to smart grids, a need emerges for grid optimization which can increase the availability and reliability of systems and increase the efficiency while reducing possible costs. Doing this requires improved system control and system optimization. With increased use of distributed generation and wireless communications, a need also emerges for more sophisticated methods to address demand response and demand-side management.

Advancements in utility control will allow essential components to be monitored to facilitate fast system diagnosis and good solutions, while increased energy storage, whether it be battery, supercapacitor or even flywheel for short term storage, will help to smooth operation and permit more intermittent distributed generation. To coordinate this, real-time control is required, and information and data exchanged to optimize the system; asset utilization and security are also needed. New loads, such as electric vehicle charging, will additionally come to the fore.

This Special Issue welcomes papers that address:

Control and optimization in smart grids and in particular the control of increased distributed energy generation;
Use of storage devices;
Inclusion of electric vehicles;
Improvement in flexible AC transmission system devices;
Use of “intelligent” appliances and even intelligent buildings;
Reconfiguration of power systems into linked smart and microgrids rather than embedded centralized generation grids;
Studies on microgrid control down to domestic application.

Prof. Dr. David Dorrell
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

smart grids
control
optimization
microgrids
distributed generation
energy storage

Related Special Issue

Smart Grid Control and Optimization in Energies (10 articles)

Published Papers (3 papers)

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Research

30 pages, 3142 KiB

Open AccessArticle

Balancing of Low-Voltage Supply Network with a Smart Utility Controller Leveraging Distributed Customer Energy Sources

by Dumisani Mtolo, David Dorrell and Rudiren Pillay Carpanen

Energies 2023, 16(23), 7707; https://doi.org/10.3390/en16237707 - 22 Nov 2023

Viewed by 702

Abstract

In South Africa, there has been a rapid adoption of solar power, particularly inverter-based solar sources, in low-voltage (LV) networks due to factors such as load shedding, rising electricity costs and greenhouse gas emissions reduction. In residential LV networks, the alignment between solar supply and energy demand is less precise, necessitating larger battery storage systems to effectively utilize solar energy. Residential areas experience peak energy demand in the morning and evening when solar irradiance is limited. As a result, substantial energy storage is important to fully utilize the potential of solar energy. However, increasing inverter-based, customer-generated power creates an imbalance in the utility supply. This is because utility LV supply transformers have three phases, while individual customers have single-phase connections and no load balancing control mechanism. This supply imbalance adversely affects the overall power quality, causing energy losses, damage to devices and other issues. To address these problems, the paper proposes a smart control approach to minimize power imbalances within utility LV supply transformers. The controller uses customer battery storage in residential areas to balance the utility transformer phases. A laboratory model was built to simulate a three-phase low-voltage network with single-phase customers, both with and without a smart controller. The results show that closely monitoring and controlling individual inverters through a central controller can significantly improve the balance of the supply network. Full article

(This article belongs to the Special Issue Smart Grid Control and Optimization (Volume II))

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25 pages, 417 KiB

Open AccessArticle

Review of Cyberattack Implementation, Detection, and Mitigation Methods in Cyber-Physical Systems

by Namhla Mtukushe, Adeniyi K. Onaolapo, Anuoluwapo Aluko and David G. Dorrell

Energies 2023, 16(13), 5206; https://doi.org/10.3390/en16135206 - 6 Jul 2023

Cited by 5 | Viewed by 2440

Abstract

With the rapid proliferation of cyber-physical systems (CPSs) in various sectors, including critical infrastructure, transportation, healthcare, and the energy industry, there is a pressing need for robust cybersecurity mechanisms to protect these systems from cyberattacks. A cyber-physical system is a combination of physical and cyber components, and a security breach in either component can lead to catastrophic consequences. Cyberattack detection and mitigation methods in CPSs involve the use of various techniques such as intrusion detection systems (IDSs), firewalls, access control mechanisms, and encryption. Overall, effective cyberattack detection and mitigation methods in CPSs require a comprehensive security strategy that considers the unique characteristics of a CPS, such as the interconnectedness of physical and cyber components, the need for real-time response, and the potential consequences of a security breach. By implementing these methods, CPSs can be better protected against cyberattacks, thus ensuring the safety and reliability of critical infrastructure and other vital systems. This paper reviews the various kinds of cyber-attacks that have been launched or implemented in CPSs. It reports on the state-of-the-art detection and mitigation methods that have been used or proposed to secure the safe operation of various CPSs. A summary of the requirements that CPSs need to satisfy their operation is highlighted, and an analysis of the benefits and drawbacks of model-based and data-driven techniques is carried out. The roles of machine learning in cyber assault are reviewed. In order to direct future study and motivate additional investigation of this increasingly important subject, some challenges that have been unaddressed, such as the prerequisites for CPSs, an in-depth analysis of CPS characteristics and requirements, and the creation of a holistic review of the different kinds of attacks on different CPSs, together with detection and mitigation algorithms, are discussed in this review. Full article

(This article belongs to the Special Issue Smart Grid Control and Optimization (Volume II))

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20 pages, 4907 KiB

Open AccessArticle

Experimental Performance Analysis of Hardware-Based Link Quality Estimation Modelling Applied to Smart Grid Communications

by Natthanan Tangsunantham and Chaiyod Pirak

Energies 2023, 16(11), 4326; https://doi.org/10.3390/en16114326 - 25 May 2023

Cited by 1 | Viewed by 829

Abstract

The smart grid is the modern electricity grid, which significantly improves the efficiency, reliability, and sustainability of electricity transmission systems. The advanced metering infrastructure (AMI) system, which is the essential system in the smart grid, enables real-time data collection and data analysis obtained from smart meters (SMs) and other devices through last-mile communication networks. In this paper, the hardware-based link quality estimation (LQE) was modeled, namely an SNR-based model, a mapping model, and an RSSI- and PRR-based logistic regression model, and their performance was then evaluated by the root mean-squared error (RMSE) with the empirical data. The SNR-based and mapping models were formulated by the packet error probability, whereas the RSSI- and PRR-based logistic regression model was formulated by the empirical data fitting. The RSSI- and PRR-based logistic regression model outperformed the other two models, with an RMSE difference of 111–122%. These LQE models can be implemented on SMs or modems to monitor the reliability and efficiency of the AMI last-mile communication network. Full article

(This article belongs to the Special Issue Smart Grid Control and Optimization (Volume II))

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