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Modeling and Simulation for the Electrical Power System
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Modeling and Simulation for the Electrical Power System

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 32959

Special Issue Editors

Prof. Dr. Dongsheng Yu

E-Mail Website
Guest Editor
School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: power converters; renewable generation; nonlinear circuits and its application; high power EV charger
Special Issues, Collections and Topics in MDPI journals
Dr. Muhammad Junaid

E-Mail Website
Guest Editor
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: high voltage power equipment; machine learning techniques in high voltage engineering; arc modeling; cryogenic dielectrics; superconducting power devices for power grid; SF6 gas alternatives
Special Issues, Collections and Topics in MDPI journals
Dr. Samson Yu

E-Mail Website
Guest Editor
School of Engineering, Deakin University, Geelong, VIC 3216, Australia
Interests: nonlinear systems; optimization; control theories and applications; sustainable transportation and electricity
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yihua Hu

E-Mail Website
Guest Editor
Department of Electronic Engineering, University of York, Heslington, York YO10 5DD, UK
Interests: renewable generation; power electronics converters & control; electric vehicle; more electric ship/aircraft; smart energy system and non-destructive test technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modeling and simulation have gained significant importance in modern complex systems. The modern electrical power system is one of the wonders of this fast-growing world and one of the most complex and sophisticated network systems. Innovations in the modeling and simulation of electrical power systems have led to significant improvements for fault detection, turnaround time of system design, the scheduling and control of power generation units, and the overall efficiency and safety of electrical power systems. This has attracted great research attention in the development of modeling and simulation technologies for electrical power systems.

Thus, to highlight the latest solutions and paradigms in the modeling and simulation of electrical power systems, this Special Issue, entitled: “Modeling and Simulation for the Electrical Power System”, is proposed for the Mathematics journal published by MDPI. It is an international, peer-reviewed, open access journal indexed by several renowned databases, such as WOS (SCIE Impact Factor 2.258, Q1) and SCOPUS (Elsevier). This Special Issue aims to publish the latest and innovative research works in the field of modeling and simulation for electrical power systems, supported by state-of-the-art studies. Topics for this special issue include, but are not limited to, the following:

  • Modeling and simulation for modern power systems with highly penetrated power converters;
  • Modeling for power converters interfaced with renewable energy generation;
  • New algorithms for improving modeling and simulation;
  • Machine learning techniques used in electrical power systems;
  • Numerical and physical arc modeling in electrical power systems;
  • Simulation solutions for high-frequency power converters;
  • Simulation-based design of energy storage systems and EV chargers;
  • Fault detection and diagnosis for electrical power systems;
  • Nonlinear behaviors in electrical power systems;
  • Stability control for electrical power systems;
  • Simulation solutions for motor design and control;
  • Modeling and simulation for distributed generation and microgrids;
  • Simulation-based studies for electrical power systems, including dynamics modeling, estimation, and control.

Prof. Dr. Dongsheng Yu
Dr. Muhammad Junaid
Dr. Samson Yu
Prof. Dr. Yihua Hu
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. Mathematics 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

  • power system modeling
  • numerical and physical arc modeling
  • machine learning in power systems
  • power converters modeling
  • power systems operations and control
  • modeling and simulations of superconducting power devices
  • energy storages system and EV chargers
  • fault detection and diagnosis
  • distributed generation and microgrids
  • motor design and control

Published Papers (19 papers)

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Research

22 pages, 3562 KiB  
Article
Increasing Distributed Generation Hosting Capacity Based on a Sequential Optimization Approach Using an Improved Salp Swarm Algorithm
by Andrei M. Tudose, Dorian O. Sidea, Irina I. Picioroaga, Nicolae Anton and Constantin Bulac
Mathematics 2024, 12(1), 48; https://doi.org/10.3390/math12010048 - 22 Dec 2023
Cited by 1 | Viewed by 495
Abstract
In recent years, a pronounced transition to the exploitation of renewable energy sources has be observed worldwide, driven by current climate concerns and the scarcity of conventional fuels. However, this paradigm shift is accompanied by new challenges for existing power systems. Therefore, the [...] Read more.
In recent years, a pronounced transition to the exploitation of renewable energy sources has be observed worldwide, driven by current climate concerns and the scarcity of conventional fuels. However, this paradigm shift is accompanied by new challenges for existing power systems. Therefore, the hosting capacity must be exhaustively assessed in order to maximize the penetration of distributed generation while mitigating any adverse impact on the electrical grid in terms of voltage and the operational boundaries of the equipment. In this regard, multiple aspects must be addressed in order to maintain the proper functioning of the system following the new installations’ capacities. This paper introduces a sequential methodology designed to determine the maximum hosting capacity of a power system through the optimal allocation of both active and reactive power. To achieve this goal, an Improved Salp Swarm Algorithm is proposed, aiming to establish the appropriate operational planning of the power grid considering extensive distributed generation integration, while still ensuring a safe operation. The case study validates the relevance of the proposed model, demonstrating a successful enhancement of hosting capacity by 14.5% relative to standard models. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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24 pages, 15757 KiB  
Article
Finite Control Set Model Predictive Control (FCS-MPC) for Enhancing the Performance of a Single-Phase Inverter in a Renewable Energy System (RES)
by Chang-Hua Lin, Shoeb Azam Farooqui, Hwa-Dong Liu, Jian-Jang Huang and Mohd Fahad
Mathematics 2023, 11(21), 4553; https://doi.org/10.3390/math11214553 - 5 Nov 2023
Cited by 1 | Viewed by 1434
Abstract
A single-phase five-level T-type topology has been investigated in this article. This topology has emerged as a viable option for renewable energy systems (RES) due to its inherent benefits. The finite control set model predictive control (FCS-MPC) strategy has been implemented to this [...] Read more.
A single-phase five-level T-type topology has been investigated in this article. This topology has emerged as a viable option for renewable energy systems (RES) due to its inherent benefits. The finite control set model predictive control (FCS-MPC) strategy has been implemented to this topology in order to improve the performance and overall reliability of the system. This control strategy empowers the inverter to predict future behavior based on a discrete set of control signals, enabling precise modulation and high-speed response to system dynamics. In the realm of RES, integration of FCS-MPC with multilevel inverters (MLIs) holds great potential to enhance energy conversion efficiency, grid integration, and overall system reliability. The article is structured to present an overview of the evolving landscape of power electronic systems, and the advantages of FCS-MPC. This paper provides a comprehensive analysis of the FCS-MPC control strategy applied to the single-phase five-level T-type topology. The study covers various aspects including the theoretical framework, hardware development, and experimental evaluation. It is obvious from the analysis that this inverter topology is reliable. Several redundant states make it fault-tolerant which helps in maintaining the output voltage at the same level even in the fault conditions. Additionally, the results show that the output load voltage is maintained at the same level irrespective of load change. Also, output load voltage has maintained the high-quality sinusoidal characteristics as the total harmonic distortion (THD) is very low. With all these features, this system is suitable within the framework of RES. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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19 pages, 10616 KiB  
Article
A Novel DC Electronic Load Topology Incorporated with Model Predictive Control Approach
by Mohammad Suhail Khan, Chang-Hua Lin, Javed Ahmad, Mohammad Fahad and Hwa-Dong Liu
Mathematics 2023, 11(15), 3353; https://doi.org/10.3390/math11153353 - 31 Jul 2023
Viewed by 895
Abstract
This paper presents a novel topology of a modified isolated single-ended-primary-inductance converter (SEPIC) with a model predictive control (MPC) approach applied to direct current (DC) electronic loads. The proposed converter uses an actual transformer rather than a coupled inductor for isolation between the [...] Read more.
This paper presents a novel topology of a modified isolated single-ended-primary-inductance converter (SEPIC) with a model predictive control (MPC) approach applied to direct current (DC) electronic loads. The proposed converter uses an actual transformer rather than a coupled inductor for isolation between the source and the load. The transformer allows the proposed converter to operate at a higher switching frequency, ultimately reducing the passive components’ size. A low-power hardware prototype is developed and tested with a model predictive control algorithm under variable input voltages and load conditions. The performance of the proposed converter is demonstrated to be satisfactory under steady state, as well as sudden input voltage transients. The proposed converter utilizes a switched capacitor technique to generate alternating current in both windings of the transformer. As the coupled inductor is eliminated from the circuit, the problem of high voltage spikes occurring due to leakage inductances is also eliminated for the proposed converter. Therefore, the proposed converter can be used for isolated medium power applications. The experimental results show that the efficiency of the proposed converter reached 96%. The MPC allows this converter’s DC voltage level to remain stable even as the input voltage and output terminal load change. Lastly, this converter with an MPC approach can be applied to different DC electronic loads, improving DC power quality and DC electronic load life. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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20 pages, 5750 KiB  
Article
An Ensemble Deep Learning Model for Provincial Load Forecasting Based on Reduced Dimensional Clustering and Decomposition Strategies
by Kaiyan Wang, Haodong Du, Jiao Wang, Rong Jia and Zhenyu Zong
Mathematics 2023, 11(12), 2786; https://doi.org/10.3390/math11122786 - 20 Jun 2023
Viewed by 1231
Abstract
The accurate prediction of short-term load is crucial for the grid dispatching department in developing power generation plans, regulating unit output, and minimizing economic losses. However, due to the variability in customers’ electricity consumption behaviour and the randomness of load fluctuations, it is [...] Read more.
The accurate prediction of short-term load is crucial for the grid dispatching department in developing power generation plans, regulating unit output, and minimizing economic losses. However, due to the variability in customers’ electricity consumption behaviour and the randomness of load fluctuations, it is challenging to achieve high prediction accuracy. To address this issue, we propose an ensemble deep learning model that utilizes reduced dimensional clustering and decomposition strategies to mitigate large prediction errors caused by non-linearity and unsteadiness of load sequences. The proposed model consists of three steps: Firstly, the selected load features are dimensionally reduced using singular value decomposition (SVD), and the principal features are used for clustering different loads. Secondly, variable mode decomposition (VMD) is applied to decompose the total load of each class into intrinsic mode functions of different frequencies. Finally, an ensemble deep learning model is developed by combining the strengths of LSTM and CNN-GRU deep learning algorithms to achieve accurate load forecasting. To validate the effectiveness of our proposed model, we employ actual residential electricity load data from a province in northwest China. The results demonstrate that the proposed algorithm performs better than existing methods in terms of predictive accuracy. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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18 pages, 7784 KiB  
Article
A Robust Fractional-Order Control Scheme for PV-Penetrated Grid-Connected Microgrid
by Nikhil Pachauri, Vigneysh Thangavel, Velamuri Suresh, Mvv Prasad Kantipudi, Hossam Kotb, Ravi Nath Tripathi and Mohit Bajaj
Mathematics 2023, 11(6), 1283; https://doi.org/10.3390/math11061283 - 7 Mar 2023
Cited by 9 | Viewed by 1405
Abstract
This article presents a new cascaded control strategy to control the power flow in a renewable-energy-based microgrid operating in grid-connected mode. The microgrid model is composed of an AC utility grid interfaced with a multi-functional grid interactive converter (MF-GIC) acting as a grid-forming [...] Read more.
This article presents a new cascaded control strategy to control the power flow in a renewable-energy-based microgrid operating in grid-connected mode. The microgrid model is composed of an AC utility grid interfaced with a multi-functional grid interactive converter (MF-GIC) acting as a grid-forming converter, a photovoltaic (PV) power-generation system acting as grid-feeding distributed generation unit, and various sensitive/non-sensitive customer loads. The proposed control strategy consists of a fractional order PI (FO-PI) controller to smoothly regulate the power flow between the utility grid, distributed generation unit, and the customers. The proposed controller exploits the advantages of FO (Fractional Order) calculus in improving the steady-state and dynamic performance of the renewable-energy-based microgrid under various operating conditions and during system uncertainties. To tune the control parameters of the proposed controller, a recently developed evaporation-rate-based water-cycle algorithm (ERWCA) is utilized. The performance of the proposed control strategy is tested under various operating conditions to show its efficacy over the conventional controller. The result shows that the proposed controller is effective and robust in maintaining all the system parameters within limits under all operating conditions, including system uncertainties. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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31 pages, 8590 KiB  
Article
Modified Analytical Technique for Multi-Objective Optimal Placement of High-Level Renewable Energy Penetration Connected to Egyptian Power System
by Mahmoud Aref, Vladislav Oboskalov, Adel El-Shahat and Almoataz Y. Abdelaziz
Mathematics 2023, 11(4), 958; https://doi.org/10.3390/math11040958 - 13 Feb 2023
Cited by 2 | Viewed by 1479
Abstract
The 2022 United Nations Climate Change Conference (COP27) recommended that Egypt be converted to green energy, in addition to increasing the demand for annual energy consumption, which will lead to an increase in the use of renewable energy sources (RES) in Egypt. The [...] Read more.
The 2022 United Nations Climate Change Conference (COP27) recommended that Egypt be converted to green energy, in addition to increasing the demand for annual energy consumption, which will lead to an increase in the use of renewable energy sources (RES) in Egypt. The Egyptian Ministry of Energy and Electricity plans to build RES (photovoltaic systems and wind farms) connected to the Egyptian power system (EPS). It is a defect to choose the position and size of the RES based on only power calculations because the RES is an intermittent source. This paper presents a modified analytical energy technique for locating RES in IEEE 33-bus and 69-bus distribution networks and a realistic 25-bus 500 kV EPS. An analytical multi-objective function has been developed to determine the optimal locations of DGs or RESs based on power losses and annual energy loss calculations of the system depending on weather conditions. The efficiency and feasibility of the proposed algorithm based on the IEEE 33-bus and 69-bus distribution networks and the realistic 25-bus 500 kV EPS have been tested and compared with PSO and GA. The impact of RESs on the performance of the 25-bus 500 kV EPS has been investigated based on annual energy losses and operation stability depending on weather conditions. The results showed that the proposed technique used these effective values to obtain optimal weather-adjusted locations. The optimal locations of PV systems or wind systems based on energy calculation improved the voltage profile better than power calculation by about 2%, and the annual energy losses decreased by about 7%. The performance of the 25-bus 500 kV EPS, due to the addition of RES, resulted in a decrease in the annual energy losses of 47% and an improvement in the voltage profile and system stability. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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20 pages, 12337 KiB  
Article
Progressive Hybrid-Modulated Network for Single Image Deraining
by Xiaoyuan Yu, Guidong Zhang, Fei Tan, Fengguo Li and Wei Xie
Mathematics 2023, 11(3), 691; https://doi.org/10.3390/math11030691 - 29 Jan 2023
Cited by 2 | Viewed by 1457
Abstract
Rainy degeneration damages an image’s visual effect and influences the performance of subsequent vision tasks. Various deep learning methods for single image deraining have been proposed, obtaining appropriate recovery results. Unfortunately, most existing methods ignore the interaction between rain-layer and rain-free components when [...] Read more.
Rainy degeneration damages an image’s visual effect and influences the performance of subsequent vision tasks. Various deep learning methods for single image deraining have been proposed, obtaining appropriate recovery results. Unfortunately, most existing methods ignore the interaction between rain-layer and rain-free components when extracting relevant features, leading to undesirable results. To break the above limitations, we propose a progressive hybrid-modulated network (PHMNet) for single image deraining based on the two-branch and coarse-to-fine framework. Specifically, a hybrid-modulated module (HMM) with a two-branch framework is proposed to blend and modulate the feature of rain-free layers and rain streaks. After cascading several HMMs in the coarsest reconstructed stage of the PHMNet, a multi-level refined module (MLRM) is adopted to refine the final deraining results in the refined reconstructed stage. By being trained using loss functions such as contrastive learning, the PHMNet can obtain satisfactory deraining results. Extended experiments on several datasets and downstream tasks demonstrate that our method performs favorably against state-of-the-art methods in quantitative evaluation and visual effects. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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15 pages, 2308 KiB  
Article
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
by Mihail Senyuk, Murodbek Safaraliev, Firuz Kamalov and Hana Sulieman
Mathematics 2023, 11(3), 525; https://doi.org/10.3390/math11030525 - 18 Jan 2023
Cited by 10 | Viewed by 3011
Abstract
This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. [...] Read more.
This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic stability assessment is achieved. The selected research topic relates to the issue of changing the structure and parameters of modern power systems. The key features of modern power systems include the following: decreased total inertia caused by integration of renewable sources energy, stricter requirements for emergency control accuracy, highly digitized operation and control of power systems, and high volumes of data that describe power system operation. Arranging emergency control in these new conditions is one of the prominent problems in modern power systems. In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. Transient stability of a power system was analyzed as the base function. Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. In the case of the test sample, accuracy of instability classification for XGBoost was 91.5%, while that for Random Forest was 81.6%. The accuracy of algorithms increased by 10.9% and 1.5%, respectively, when the topology of the power system was taken into account. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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19 pages, 3000 KiB  
Article
Statistical Method of Low Frequency Oscillations Analysis in Power Systems Based on Phasor Measurements
by Mihail Senyuk, Mohamed F. Elnaggar, Murodbek Safaraliev, Firuz Kamalov and Salah Kamel
Mathematics 2023, 11(2), 393; https://doi.org/10.3390/math11020393 - 12 Jan 2023
Cited by 2 | Viewed by 1918
Abstract
This study aims to develop and test a new accelerated method for analyzing low-frequency oscillations in power systems using phasor measurements. The proposed method is based on the use of mathematical statistics methods that do not require significant computing power and have high [...] Read more.
This study aims to develop and test a new accelerated method for analyzing low-frequency oscillations in power systems using phasor measurements. The proposed method is based on the use of mathematical statistics methods that do not require significant computing power and have high reliability. Changes in the structure of power generation and integration of control devices based on power electronics cause low-frequency oscillations of power system operation parameters that present a threat. These changes result in a reduction in the total inertia of power systems with the subsequent impact on the operation of automatic voltage regulators and power system stabilizers, the purpose of which is to damp low-frequency oscillations. We conduct a careful review of the existing methods for low-frequency oscillations analysis in power systems to identify the gaps in the literature and design a new method to address the issues. The proposed method is tested on real-life data that was obtained during a disturbance with a transient event. Estimation of the low-frequency oscillation parameters was carried out, and the potential threat posed by these phenomena was examined. The implementation of the proposed algorithm for analyzing low-frequency oscillations is done using the Matlab programming language. Evaluation of the proposed algorithm is performed on physical data obtained during real transient processes occurring at large power plants. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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13 pages, 7033 KiB  
Article
An Optimized Control Method of Soft-Switching and No Backflow Power for LLC Resonant-Type Dual-Active-Bridge DC-DC Converters
by Zimeng Li, Mingxue Li, Yushun Zhao, Zixiang Wang, Dongsheng Yu and Ruidong Xu
Mathematics 2023, 11(2), 287; https://doi.org/10.3390/math11020287 - 5 Jan 2023
Cited by 1 | Viewed by 1566
Abstract
The LLC-type resonant dual-active-bridge (LLC-DAB) DC-DC converter with a high voltage gain, high power density, and low backflow power has attracted increasing attention in recent years. However, its soft-switching and backflow power problems are still not solved, so the improvements to these problems [...] Read more.
The LLC-type resonant dual-active-bridge (LLC-DAB) DC-DC converter with a high voltage gain, high power density, and low backflow power has attracted increasing attention in recent years. However, its soft-switching and backflow power problems are still not solved, so the improvements to these problems are studied in this paper. Based on the dual phase shift (DPS) modulation method, the operating characteristics are analyzed, and a soft-switching and no backflow power modulation curve is established based on the voltage-current time-domain characteristics. On this basis, a soft-switching and no backflow power optimized control method based on DPS modulation is proposed to achieve soft-switching operation and eliminate backflow power. Due to the complex time-domain characteristics of the resonant tank voltage and current, the relationship between the phase shift ratios is fitted and optimized with this method based on the soft-switching and no backflow power characteristic curve, and the optimized results of the phase shift ratio under different operating conditions are obtained. The simulation results indicate that the soft-switching operation of the LLC-DAB converter can be achieved with the optimized control method proposed in this paper, and the backflow power is effectively eliminated. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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30 pages, 5768 KiB  
Article
Reduction in Voltage Harmonics of Parallel Inverters Based on Robust Droop Controller in Islanded Microgrid
by Sultan Alghamdi, Hatem F. Sindi, Ahmed Al-Durra, Abdullah Ali Alhussainy, Muhyaddin Rawa, Hossam Kotb and Kareem M. AboRas
Mathematics 2023, 11(1), 172; https://doi.org/10.3390/math11010172 - 29 Dec 2022
Cited by 3 | Viewed by 2086
Abstract
In this article, a distributed control scheme to compensate for voltage harmonics in islanded microgrids is presented, where each distributed generation (DG) source has a primary control level and a secondary control level. In addition to the voltage and current control loops, the [...] Read more.
In this article, a distributed control scheme to compensate for voltage harmonics in islanded microgrids is presented, where each distributed generation (DG) source has a primary control level and a secondary control level. In addition to the voltage and current control loops, the primary control level of DGs includes virtual impedance control loops in the main and harmonic components, which are responsible for dividing the power of the main component and the non-main component (harmonic) between the DGs of the microgrid, respectively. For coordinated operation between the inverters when facing the islanding phenomenon, it is very beneficial to use a droop controller structure. Here, the traditional droop controller is modified in such a way that the power is proportionally divided between the DGs, which causes accurate voltage regulation at the output of the DGs. By presenting a model for the inverter connected to the nonlinear load, a harmonic droop controller is designed. Through the droop controller related to each harmonic, the harmonic voltages are calculated and added to the reference voltage, which improves the quality of the output voltage. Then, the inverter voltage control loop is modified with resistive impedance in the presence of nonlinear loads in such a way that, when combined with the harmonic droop controller, the total harmonic distortion (THD) of the output voltage is significantly reduced. Lastly, the proposed method is implemented on the microgrid through MATLAB software, and the results show the ability of the proposed method to reduce voltage harmonics in the parallel operation of inverters. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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24 pages, 5572 KiB  
Article
Two-Stage Optimal Active-Reactive Power Coordination for Microgrids with High Renewable Sources Penetration and Electrical Vehicles Based on Improved Sine−Cosine Algorithm
by Dorian O. Sidea, Andrei M. Tudose, Irina I. Picioroaga and Constantin Bulac
Mathematics 2023, 11(1), 45; https://doi.org/10.3390/math11010045 - 22 Dec 2022
Cited by 2 | Viewed by 1225
Abstract
As current global trends aim at the large-scale insertion of electric vehicles as a replacement for conventional vehicles, new challenges occur in terms of the stable operation of electric distribution networks. Microgrids have become reliable solutions for integrating renewable energy sources, such as [...] Read more.
As current global trends aim at the large-scale insertion of electric vehicles as a replacement for conventional vehicles, new challenges occur in terms of the stable operation of electric distribution networks. Microgrids have become reliable solutions for integrating renewable energy sources, such as solar and wind, and are considered a suitable alternative for accommodating the growing fleet of electrical vehicles. However, efficient management of all equipment within a microgrid requires complex solving algorithms. In this article, a novel two-stage scheme is proposed for the optimal coordination of both active and reactive power flows in a microgrid, considering the high penetration of renewable energy sources, energy storage systems, and electric mobility. An improved sine-cosine algorithm is introduced to ensure the day-ahead optimal planning of the microgrid’s components aiming at minimizing the total active energy losses of the system. In this regard, both local and centralized control strategies are investigated for multiple generations and consumption scenarios. The latter proved itself a promising control scheme for the microgrid operation, as important energy loss reduction is encountered when applied. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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18 pages, 2602 KiB  
Article
Advanced Algorithms in Automatic Generation Control of Hydroelectric Power Plants
by Yury V. Kazantsev, Gleb V. Glazyrin, Alexandra I. Khalyasmaa, Sergey M. Shayk and Mihail A. Kuparev
Mathematics 2022, 10(24), 4809; https://doi.org/10.3390/math10244809 - 17 Dec 2022
Cited by 3 | Viewed by 1727
Abstract
The problem of load distribution between hydraulic units at hydropower plants is a difficult task due to the nonlinearity of hydro turbine characteristics and individual peculiarities of the generation units, in which operating conditions are often different. It is necessary to apply the [...] Read more.
The problem of load distribution between hydraulic units at hydropower plants is a difficult task due to the nonlinearity of hydro turbine characteristics and individual peculiarities of the generation units, in which operating conditions are often different. It is necessary to apply the most up-to-date optimization methods that take into account the nonlinearity of the turbine characteristics. The methods must also consider strict constraints on the operation conditions of the power equipment when searching for the extremum of the objective function specified in the form of equalities and inequalities. When solving the aforementioned optimization problem, the constraints on computing capacities of the digital automatic generation control systems that must operate in real-time mode were taken into account. To solve the optimization task, the interior point method was analyzed and the method of Lagrange multipliers was modified so that it could minimize turbine discharge and active energy losses in the windings of the power generators and unit power transformers. The article presents the simulation results of the developed optimization algorithms and the results of the field tests of the automatic generation control system executing the proposed algorithms. All of the tests showed a fairly high efficiency of the proposed optimization methods in real operation conditions. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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20 pages, 14502 KiB  
Article
Design and Experimental Verification of a General Single-Switch N-Stage Z-Network High Gain Boost Converter
by Xiaoyi Liu, Samson Shenglong Yu, Guidong Zhang, Weiqun Lin, Tao Liu and Weiping Le
Mathematics 2022, 10(24), 4758; https://doi.org/10.3390/math10244758 - 14 Dec 2022
Cited by 1 | Viewed by 1021
Abstract
A single-switch N-stage Z-network high-gain boost converter is proposed in this study, which can be applied in the field of chip etching for bias provision. The circuit topology, operation mode, voltage gain and the control strategy are analyzed. Thereafter, the steady-state performance of [...] Read more.
A single-switch N-stage Z-network high-gain boost converter is proposed in this study, which can be applied in the field of chip etching for bias provision. The circuit topology, operation mode, voltage gain and the control strategy are analyzed. Thereafter, the steady-state performance of the circuit is analyzed with small signal stability modeling. A simulation model is built using Simulink and compared with the traditional quadratic circuit. Combined with the control strategy, the circuit can obtain better steady-state performance by controlling the number of working N-networks and adjusting the duty ratio in the case of high voltage, wide range of voltage output and dynamic voltage output. The simulation model and hardware prototype of the single-switch four-stage Z-network high-gain boost circuit are built and tested, which have verified the effectiveness of the proposed design. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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17 pages, 1376 KiB  
Article
Daily Peak-Electricity-Demand Forecasting Based on Residual Long Short-Term Network
by Hyunsoo Kim, Jiseok Jeong and Changwan Kim
Mathematics 2022, 10(23), 4486; https://doi.org/10.3390/math10234486 - 28 Nov 2022
Cited by 6 | Viewed by 1691
Abstract
Forecasting the electricity demand of buildings is a key step in preventing a high concentration of electricity demand and optimizing the operation of national power systems. Recently, the overall performance of electricity-demand forecasting has been improved through the application of long short-term memory [...] Read more.
Forecasting the electricity demand of buildings is a key step in preventing a high concentration of electricity demand and optimizing the operation of national power systems. Recently, the overall performance of electricity-demand forecasting has been improved through the application of long short-term memory (LSTM) networks, which are well-suited to processing time-series data. However, previous studies have focused on improving the accuracy in forecasting only overall electricity demand, but not peak demand. Therefore, this study proposes adding residual learning to the LSTM approach to improve the forecast accuracy of both peak and total electricity demand. Using a residual block, the residual LSTM proposed in this study can map the residual function, which is the difference between the hypothesis and the observed value, and subsequently learn a pattern for the residual load. The proposed model delivered root mean square errors (RMSE) of 10.5 and 6.91 for the peak and next-day electricity demand forecasts, respectively, outperforming the benchmark models evaluated. In conclusion, the proposed model provides highly accurate forecasting information, which can help consumers achieve an even distribution of load concentration and countries achieve the stable operation of the national power system. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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19 pages, 2467 KiB  
Article
Fast Algorithms for Estimating the Disturbance Inception Time in Power Systems Based on Time Series of Instantaneous Values of Current and Voltage with a High Sampling Rate
by Mihail Senyuk, Svetlana Beryozkina, Pavel Gubin, Anna Dmitrieva, Firuz Kamalov, Murodbek Safaraliev and Inga Zicmane
Mathematics 2022, 10(21), 3949; https://doi.org/10.3390/math10213949 - 24 Oct 2022
Cited by 16 | Viewed by 1203
Abstract
The study examines the development and testing of algorithms for disturbance inception time estimation in a power system using instantaneous values of current and voltage with a high sampling rate. The algorithms were tested on both modeled and physical data. The error of [...] Read more.
The study examines the development and testing of algorithms for disturbance inception time estimation in a power system using instantaneous values of current and voltage with a high sampling rate. The algorithms were tested on both modeled and physical data. The error of signal extremum forecast, the error of signal form forecast, and the signal value at the so-called joint point provided the basis for the suggested algorithms. The method of tuning for each algorithm was described. The time delay and accuracy of the algorithms were evaluated with varying tuning parameters. The algorithms were tested on the two-machine model of a power system in Matlab/Simulink. Signals from emergency event recorders installed on real power facilities were used in testing procedures. The results of this study indicated a possible and promising application of the suggested methods in the emergency control of power systems. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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12 pages, 2205 KiB  
Article
Research on a Real-Time Monitoring Method for the Three-Dimensional Straightness of a Scraper Conveyor Based on Binocular Vision
by Jiakun Lv, Peng Shi, Zhijun Wan, Jingyi Cheng, Keke Xing, Mingli Wang and Hong Gou
Mathematics 2022, 10(19), 3545; https://doi.org/10.3390/math10193545 - 28 Sep 2022
Cited by 5 | Viewed by 1446
Abstract
Measuring the straightness of the scraper conveyor, which is an indispensable piece of equipment in a fully mechanized coal face, can prevent accidents such as derailment of the shearer and is also important for the precise positioning of the shearer and the accurate [...] Read more.
Measuring the straightness of the scraper conveyor, which is an indispensable piece of equipment in a fully mechanized coal face, can prevent accidents such as derailment of the shearer and is also important for the precise positioning of the shearer and the accurate control of the hydraulic support. The existing scraper conveyor straightness measurement methods have the disadvantages of inconsistent measurement cost, accuracy, and reliability as well as low dimension of straightness description. To this end, this paper proposes a method for monitoring the three-dimensional straightness of a scraper conveyor based on binocular vision. Trapezoidal window matching technology was used to realize the image acquisition of multiple stations and multiple sensors. The bit pose acquisition model of binocular vision 3D reconstruction was used to obtain the 3D coordinates of the feature points on the sign board in each local coordinate system and the bit pose information of each sign board. The pose relay videometric method was used to convert the straightness in each local coordinate system to the global coordinate system to realize the 3D reconstruction of the scraper conveyor. Finally, the straightness measurement test of the preset scraper conveyor was carried out, and the error analysis was carried out by comparing with the manual measurement results, which showed that the measurement errors were all within ±30 mm. At the same time, the standard deviation of errors in both directions was small, which indicates that the straightness measurement method for the scraper conveyor in this paper has high reliability. In addition, the visual measurement process is independent of each other, so there is no error accumulation in the visual straightness measurement method. The analysis shows that the method of measuring the straightness of a scraper conveyor based on binocular vision can realize continuous and real-time monitoring of the scraper conveyor. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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17 pages, 5067 KiB  
Article
Using Matlab/Simulink Software Package to Investigate Fault Behaviors in HVDC System
by Olumoroti Ikotun, Ephraim Bonah Agyekum, Emad M. Ahmed and Salah Kamel
Mathematics 2022, 10(16), 3014; https://doi.org/10.3390/math10163014 - 21 Aug 2022
Cited by 2 | Viewed by 2232
Abstract
Existing studies show that several performance issues will arise in the HVDC link during the three phase-to-ground fault at the side of the inverter and that the DC voltage will oscillate around zero and will not affect the rectifier of the AC system [...] Read more.
Existing studies show that several performance issues will arise in the HVDC link during the three phase-to-ground fault at the side of the inverter and that the DC voltage will oscillate around zero and will not affect the rectifier of the AC system though the inverter of the AC system, and the AC voltages will become zero and the AC currents will show high amplitude as well as minor disturbances. It has also been argued that when the fault is applied on a single-phase to ground fault at the inverter side on the AC side, the voltage will decrease. In this paper, we focus on single line-to-ground fault, double line-to-ground fault, and three phase-to-ground fault at the inverter of the AC system and their behavior on the DC link as well as on the AC system of the rectifier with detailed simulations. A high voltage direct current (HVDC) Monopolar system is modeled using a Matlab/Simulink software package for the research. The results show that during the three phase-to-ground fault at the AC system of the inverter, the DC voltage will increase with a bogus waveform and the currents of the AC system at the rectifier will collapse to zero.At the double phase-to-ground fault level, the DC voltage will experience an increase in waveform while the currents of the AC system of the rectifier will experience different disturbances. At the single phase-to-ground fault level, the DC voltage will remain stable and the rectifier side of the AC system will also experience a stable state for both currents and voltages. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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16 pages, 3672 KiB  
Article
Multi-Step-Ahead Electricity Price Forecasting Based on Temporal Graph Convolutional Network
by Haokun Su, Xiangang Peng, Hanyu Liu, Huan Quan, Kaitong Wu and Zhiwen Chen
Mathematics 2022, 10(14), 2366; https://doi.org/10.3390/math10142366 - 6 Jul 2022
Cited by 8 | Viewed by 1840
Abstract
Traditional electricity price forecasting tends to adopt time-domain forecasting methods based on time series, which fail to make full use of the regional information of the electricity market, and ignore the extra-territorial factors affecting electricity price within the region under cross-regional transmission conditions. [...] Read more.
Traditional electricity price forecasting tends to adopt time-domain forecasting methods based on time series, which fail to make full use of the regional information of the electricity market, and ignore the extra-territorial factors affecting electricity price within the region under cross-regional transmission conditions. In order to improve the accuracy of electricity price forecasting, this paper proposes a novel spatio-temporal prediction model, which is combined with the graph convolutional network (GCN) and the temporal convolutional network (TCN). First, the model automatically extracts the relationships between price areas through the graph construction module. Then, the mix-jump GCN is used to capture the spatial dependence, and the dilated splicing TCN is used to capture the temporal dependence and forecast electricity price for all price areas. The results show that the model outperforms other models in both one-step forecasting and multi-step forecasting, indicating that the model has superior performance in electricity price forecasting. Full article
(This article belongs to the Special Issue Modeling and Simulation for the Electrical Power System)
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