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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 (20 March 2023) | Viewed by 17559

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Prof. Dr. David Dorrell

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School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg 2000, South Africa
Interests: electric machines; motors; renewable energy; power systems
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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; and
Studies on microgrid control down to domestic application.

Prof. David Dorrell
Guest Editor

Manuscript Submission Information

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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 (Volume II) in Energies (3 articles)

Published Papers (10 papers)

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Research

17 pages, 2103 KiB

Open AccessArticle

An Electrical Power System Reconfiguration Model Based on Optimal Transmission Switching under Scenarios of Intentional Attacks

by Juan Toctaquiza, Diego Carrión and Manuel Jaramillo

Energies 2023, 16(6), 2879; https://0-doi-org.brum.beds.ac.uk/10.3390/en16062879 - 21 Mar 2023

Cited by 1 | Viewed by 1533

Abstract

Currently, operating electrical power systems (EPS) is a complex task that relies on the experience of the operators or the strength of algorithms developed for autonomous operation. The continuous operation of EPS is vulnerable to intentional cybernetic and physical attacks. With the most significant extension and distribution in the EPS, the transmission lines are most exposed to potential attacks. Before this, the entire behavior of the EPS changes, and, on occasions, a blackout can even be generated. The present investigation focused on developing a methodology for reconfiguring the power system against intentional attacks, considering the topology change through optimal switching of transmission lines (OTS) based on optimal DC flows and quantifying the contingency index, which allows for the identification of the weaknesses of the EPS. The methodology was applied to the IEEE 30−bus system, and contingencies were randomly generated, as is typical with intentional attacks. The study successfully identified the reconfiguration strategy of EPS based on OTS-DC, mitigating potential problems such as line loadability and voltage angle deviation in the nodes. Full article

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

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15 pages, 5195 KiB

Open AccessArticle

Improving the Efficiency of Environmental Temperature Control in Homes and Buildings

by Murat Kunelbayev, Yedilkhan Amirgaliyev and Talgat Sundetov

Energies 2022, 15(23), 8839; https://0-doi-org.brum.beds.ac.uk/10.3390/en15238839 - 23 Nov 2022

Cited by 2 | Viewed by 1388

Abstract

This research developed an effective environmental temperature control system for homes and buildings. The study used a photovoltaic panel (PV) and developed a solar installation with thermosiphon circulation, which has a flat solar collector and heat-insulating translucent glass with double glazing with reduced pressure. The coolant is made of thin-walled corrugated stainless pipe. The heat from the solar flux heats the liquid removed from the collector, and cold water from the siphon enters its place. There is a constant circulation of heat, which increases heat transfer efficiency by eliminating additional partitions between the panel and thermal insulation. We have also developed a solar system control controller, which includes an electronic unit with six sensors. The six sensors are controlled by the STM32 programmable Logistics Integrated circuit (FPGA), designed to monitor the entire solar system, and the drives include power relays. The performance of the photovoltaic panel and the room’s temperature change are calculated during both the simulation and testing of the controller. The standard error was 20% compared to other controllers. During the experiment, the consumption savings amounted to about 1% due to the control signal in the controller, which has a significant impact on the service life of the equipment. Full article

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

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29 pages, 4973 KiB

Open AccessArticle

Fuzzy Logic–Based Decentralized Voltage–Frequency Control and Inertia Control of a VSG-Based Isolated Microgrid System

by Baheej Alghamdi

Energies 2022, 15(22), 8401; https://0-doi-org.brum.beds.ac.uk/10.3390/en15228401 - 10 Nov 2022

Cited by 1 | Viewed by 1263

Abstract

This work proposes the use of fuzzy-logic-based voltage frequency control (VFC) and adaptive inertia to improve the frequency response of a virtual synchronous generator (VSG)-based isolated microgrid system. The joint VFC and inertial control scheme is proposed to limit frequency deviations in these isolated microgrid systems, mainly caused by the increasing penetration of intermittent distributed energy resources, which lack rotational inertia. The proposed controller uses artificial neural networks (ANN) to estimate the exponent of voltage-dependent loads and modulate the system frequency by adjusting the output voltage of the VSGs, which increases the system’s active power reserves while providing inertial control by adjusting the inertia of VSGs to minimize frequency and VSG DC-link voltage excursions. A genetic algorithm (GA)-based optimization strategy is developed to optimally adjust the parameters of the fuzzy logic controller to diminish the impact of disturbances on the system. In addition, the proposed technique is illustrated through simulations within the framework of a test system based on the CIGRE medium-voltage benchmark under various circumstances. The results of these simulations demonstrate that the proposed control strategy outperforms existing methods. Full article

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

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18 pages, 4525 KiB

Open AccessArticle

Reactive Compensation Planning in Unbalanced Electrical Power Systems

by Jair Salazar, Diego Carrión and Manuel Jaramillo

Energies 2022, 15(21), 8048; https://0-doi-org.brum.beds.ac.uk/10.3390/en15218048 - 29 Oct 2022

Cited by 1 | Viewed by 1037

Abstract

This research focuses on finding the optimal location of reactive compensation in an unbalanced electrical power system (EPS). An EPS is named unbalanced when there is uncertainty in the behaviour of the power demand, which causes changes in the voltage profile and angle of each of the electrical power phases. For this reason, using reactive compensation will improve the voltage profiles and the magnitudes of reactive power in the transmission lines. The proposed methodology uses the optimal AC power flows as a basis, which is applied to each power phase and, through this methodology, the operating conditions of the EPS are determined. Then, based on the voltage profiles of each power phase, it was possible to determine the critical nodes of the system, so that afterwards, through heuristics, it was possible to find the optimal location of the reactive compensation that independently meets the needs of each phase. To evaluate the proposed methodology, the IEEE test systems of 9, 14, 30 and 118 bus bars were used, as well as the 230 kV ring of the Ecuadorian transmission system. Finally, using the proposed methodology, it was possible to independently compensate for each of the power phases, rectifying the unbalanced voltage profiles that appeared in the EPS. Full article

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

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18 pages, 583 KiB

Open AccessArticle

Modeling and Stability Analysis of Distributed Secondary Control Scheme for Stand-Alone DC Microgrid Applications

by Anuoluwapo Aluko, Andrew Swanson, Leigh Jarvis and David Dorrell

Energies 2022, 15(15), 5411; https://0-doi-org.brum.beds.ac.uk/10.3390/en15155411 - 27 Jul 2022

Cited by 9 | Viewed by 1590

Abstract

Stand-alone DC microgrids have multiple distributed generation (DG) sources that meet the required demand (load) by using droop control to achieve load (current) sharing between the DGs. The use of droop control leads to a voltage drop at the DC bus. This paper presents a distributed secondary control scheme to simultaneously ensure current sharing between the DGs and regulate the DC bus voltage. The proposed control scheme eliminates the voltage deviation and ensures balanced current sharing by combining the voltage and current errors in the designed secondary control loop. A new flight-based artificial bee colony optimization algorithm is proposed. This selects the parameters of the distributed secondary control scheme to achieve the objectives of the proposed controller. A state–space model of the DC microgrid is developed by using eigenvalue observation to test the impacts of the proposed optimized distributed secondary controller on the stability of the DC microgrid system. A real-time test system is developed in MATLAB/Simulink and used in a Speedgoat real-time simulator to verify the performance of the proposed control scheme for real-world applications. The results show the robustness of the proposed distributed secondary control scheme in achieving balance current sharing and voltage regulation in the DC microgrid with minimal oscillations and fast response time. Full article

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

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17 pages, 9882 KiB

Open AccessArticle

Implementation of a Multiterminal Line Commutated Converter HVDC Scheme with Auxiliary Controller on South Africa’s 765 kV Corridor

by Oluwafemi Oni, Andrew Swanson, Rudiren Pillay Carpanen and Anuoluwapo Aluko

Energies 2022, 15(12), 4356; https://0-doi-org.brum.beds.ac.uk/10.3390/en15124356 - 14 Jun 2022

Viewed by 1534

Abstract

The deployment of a 765-kV transmission line on Eskom’s South African Grid marks the beginning of a new era in power industries. The integration of renewable energies by independent power producers (IPPs) leads to an infrastructural change in the stability performance of the entire grid. These developments are expected to bring about a multiterminal direct current (MTDC) system for practical implementation on this grid. Therefore, this study focuses on the dynamic response of the South African transmission grid during a system disturbance. In the carrying out of this study, the South African grid was modeled on PSCAD, and its performance was evaluated. The impact of the MTDC link on the grid’s interarea oscillation was also investigated. An additional current order controller for the MTDC link was developed, and its impact on the MTDC power transfer was analyzed. The results show a better system performance and reduced interarea power swings with the inclusion of the MTDC link. Full article

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

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18 pages, 4243 KiB

Open AccessArticle

Fuzzy Logic and Linear Programming-Based Power Grid-Enhanced Economical Dispatch for Sustainable and Stable Grid Operation in Eastern Mexico

by Esmeralda López-Garza, René Fernando Domínguez-Cruz, Fernando Martell-Chávez and Iván Salgado-Tránsito

Energies 2022, 15(11), 4069; https://0-doi-org.brum.beds.ac.uk/10.3390/en15114069 - 01 Jun 2022

Cited by 6 | Viewed by 2361

Abstract

Sustainable, stable, and cost-optimized operation of power grids must be the main objectives of power grid operators and electric utilities. The energy transition towards a preponderant green energy economy requires innovative solutions to enhance the power grid economic dispatches looking for a better allocation of the energy demand among the diverse renewable and fossil fuel energy plants. Green renewable energy systems must be preferred over fossil fuel generators when they are available. However, fossil plants are still required to be kept operational due to the variability and uncertainty of renewable energy plants. This study proposes a hybrid rational economic dispatch model that combines a cost minimization linear model enhanced with a fuzzy logic system for decision-making on wind and hydropower minimum and maximum generation levels. The model considers the intermittency of wind energy and recognizes the strategic value of hydropower as energy storage. The results of the model with real data taken from wind, hydroelectric, geothermal, nuclear, bioenergy, and fossil fuel power plants in the eastern region of Mexico show that a fairer, rational, and cost-optimized power grid economic dispatch can be achieved with the proposed approach. Full article

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

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Graphical abstract

33 pages, 4390 KiB

Open AccessArticle

Application of Artificial Intelligence in the Unit Commitment System in the Application of Energy Sustainability

by Bohumír Garlík

Energies 2022, 15(9), 2981; https://0-doi-org.brum.beds.ac.uk/10.3390/en15092981 - 19 Apr 2022

Cited by 1 | Viewed by 1480

Abstract

This article approaches the optimal solution of energy sustainability based on the use of artificial intelligence (AI). The application of renewable energy sources (RES) and unit commitment (UC) is the basic idea of this concept. Therefore, a new approach to solving the UC problem is introduced. The proposed method has a simple procedure to obtain the popular solutions in an acceptable time interval, by creating a basic model of the schedule of the state of energy units RES. It is obvious that individual consumer units, of an operational nature, take hourly performance values by performing economic evaluations on them in the sense of cost optimization. This is conducted through an artificial intelligence (AI) algorithm by optimizing the dedicated cost function, simulated by annealing. Despite the acceptable solution obtained from these two steps, another shift is proposed, called the TDD process in a given consumer area. This process in the application of AI in the system of selection of universal load TDD from hundreds of possible ones is based on the use of artificial neural networks and cluster analysis, which is represented by the application of the Kohonen map. This logical process to achieve a modified solution is a self-organizing map (SOM). It is a software tool for visualizing high-dimensional data. Converts complex, nonlinear statistical relationships (functions) between high-dimensional data to simple geometric relationships, low-dimensional representation. The output of SOM is an optimized load TDD on the basis of which the process of automatic control of UC in the local urban area is built. The results of the AI application in the case of sustainable energy solutions confirm that this UC method provides a robust solution to an almost optimal solution. Full article

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

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40 pages, 8679 KiB

Open AccessArticle

Energy Sustainability of a Cluster of Buildings with the Application of Smart Grids and the Decentralization of Renewable Energy Sources

by Bohumír Garlík

Energies 2022, 15(5), 1649; https://0-doi-org.brum.beds.ac.uk/10.3390/en15051649 - 23 Feb 2022

Cited by 5 | Viewed by 2061

Abstract

The optimal design of a building and city, including the balance of their energy performance, must include requirements from a wide range of areas, especially electrical engineering, informatics, technical equipment of buildings, construction and architecture, psychology and many other fields. It is the optimal design, simulation and modelling that are most reflected in the energy requirements of buildings while meeting the requirements of energy sustainability. The impact of buildings and cities on the environment is crucial and unmistakable. It should be emphasized that an inappropriately (architecturally or technologically) designed building with state-of-the-art control technology will still have worse properties than an optimally designed building without a control system. This inspired us to design a building energy model (BEM) with the implementation of a Smart Grid in a decentralized sustainable energy system, which is a microgrid from renewable energy sources (RES). This inspired us to conduct an analysis of simulation models (simultaneous simulations) to show the possibility of their application in the process of fully satisfying energy needs in a given urban region. The main goal is to design an original methodology for the design of smart “Nearly Zero Energy Buildings” (NZEB) and subsequent energy sustainability solutions. This led us to use Hybrid Optimization of Multiple Energy Resources (HOMER), PV*SOL (2D solar software design tool for the photovoltaic system performance), Monte Carlo and DesignBuilder. The EMB was designed based on the Six Sigma design quality management methodology. In the process of integrating Smart Grids with energy efficiency solutions for buildings, an original optimization basis was designed for smart buildings and smart urban areas. The proposed EMB was verified in an experiment. Full article

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

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21 pages, 2197 KiB

Open AccessArticle

A Comparative Assessment of Conventional and Artificial Neural Networks Methods for Electricity Outage Forecasting

by Adeniyi Kehinde Onaolapo, Rudiren Pillay Carpanen, David George Dorrell and Evans Eshiemogie Ojo

Energies 2022, 15(2), 511; https://0-doi-org.brum.beds.ac.uk/10.3390/en15020511 - 12 Jan 2022

Cited by 10 | Viewed by 1719

Abstract

The reliability of the power supply depends on the reliability of the structure of the grid. Grid networks are exposed to varying weather events, which makes them prone to faults. There is a growing concern that climate change will lead to increasing numbers and severity of weather events, which will adversely affect grid reliability and electricity supply. Predictive models of electricity reliability have been used which utilize computational intelligence techniques. These techniques have not been adequately explored in forecasting problems related to electricity outages due to weather factors. A model for predicting electricity outages caused by weather events is presented in this study. This uses the back-propagation algorithm as related to the concept of artificial neural networks (ANNs). The performance of the ANN model is evaluated using real-life data sets from Pietermaritzburg, South Africa, and compared with some conventional models. These are the exponential smoothing (ES) and multiple linear regression (MLR) models. The results obtained from the ANN model are found to be satisfactory when compared to those obtained from MLR and ES. The results demonstrate that artificial neural networks are robust and can be used to predict electricity outages with regards to faults caused by severe weather conditions. Full article

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

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