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Modeling, Simulation, and Analysis of Electrical Power Systems
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Modeling, Simulation, and Analysis of Electrical Power Systems

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

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 9178

Special Issue Editors

Dr. Vishnu Suresh

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
Interests: microgrid; energy management system; machine learning; forecasting energy; load forecasting; optimal power flow; renewable energy sources modelling; multi objective optimization
Dr. Dominika Kaczorowska

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
Interests: microgrid; computational intelligence; particle swarm optimization; energy storage

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of the journal Mathematics on Modeling, Simulation, and Analysis of Electrical Power Systems.

An electric power system is defined as a network of interconnected electrical devices, electrical components, and electrical systems which are used to generate, transmit, and distribute electric power. Power system analysis is needed to ensure the reliable, safe, and successful operation and planning of electrical power systems design. Typical power system analysis consists of three main divisions: load flow analyses, short circuit studies, and stability studies. These concepts definitely require mathematical calculations, modelling, and simulations which are carried out to verify that the electrical system can work as intended and withstand the expected stresses so that it is protected from failure.

Power system analysis, modelling, and simulation can be performed by using specialized software that is commonly used in power plants and in the manufacturing industry which involves the study of system components, performing different modeling and calculations on components, and simulating the components of the power system. It can also include studies on the modeling of the generation, transmission, and distribution of electrical power systems.

A core component of the simulation and analysis of power systems includes research into forecasting and optimization for power system planning. This includes both statistical and machine learning/deep learning models for energy sources forecasting (solar PV output forecasting, wind power output forecasting, solar irradiation forecasting, load demand forecasting etc.). Optimization covering optimal power flow, energy management and unit commitment issues can be achieved using conventional optimization algorithms and metaheuristic optimization algorithms which minimize several objectives, such as cost minimization, emissions minimization, voltage profile management and multi-objective functions of the abovementioned options.

This Special Issue invites contributions on the development of novel system modelling, simulation, and analysis related to electrical power systems. Topics of interest include, but are not limited to, optimal power flow, energy management, energy forecasting, load forecasting, optimization under uncertainty for power systems fault analysis, machine learning/deep learning for power system planning, novel metaheuristic optimization methods for optimization, short-circuit test, protective device coordination and setting analysis, harmonic analysis, dynamic and transient analysis, earthing studies, switching overvoltage studies, and insulation coordination studies.

Dr. Vishnu Suresh
Dr. Dominika Kaczorowska
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

  • mathematical modelling of power system components
  • unit commitment
  • optimization of power system operation
  • optimization under uncertainty
  • power system planning
  • forecasting of energy sources
  • forecasting of load demand
  • machine-learning-based forecasting models
  • statistical and regression-based forecasting models
  • metaheuristic optimization algorithms for energy management
  • power system analysis
  • power system modeling and simulation
  • load flow analysis
  • short circuit studies
  • power stability studies
  • electrical power systems

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Published Papers (7 papers)

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Research

19 pages, 1400 KiB  
Article
Data Imputation in Electricity Consumption Profiles through Shape Modeling with Autoencoders
by Oscar Duarte, Javier E. Duarte and Javier Rosero-Garcia
Mathematics 2024, 12(19), 3004; https://doi.org/10.3390/math12193004 - 26 Sep 2024
Viewed by 464
Abstract
In this paper, we propose a novel methodology for estimating missing data in energy consumption datasets. Conventional data imputation methods are not suitable for these datasets, because they are time series with special characteristics and because, for some applications, it is quite important [...] Read more.
In this paper, we propose a novel methodology for estimating missing data in energy consumption datasets. Conventional data imputation methods are not suitable for these datasets, because they are time series with special characteristics and because, for some applications, it is quite important to preserve the shape of the daily energy profile. Our answer to this need is the use of autoencoders. First, we split the problem into two subproblems: how to estimate the total amount of daily energy, and how to estimate the shape of the daily energy profile. We encode the shape as a new feature that can be modeled and predicted using autoencoders. In this way, the problem of imputation of profile data are reduced to two relatively simple problems on which conventional methods can be applied. However, the two predictions are related, so special care should be taken when reconstructing the profile. We show that, as a result, our data imputation methodology produces plausible profiles where other methods fail. We tested it on a highly corrupted dataset, outperforming conventional methods by a factor of 3.7. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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26 pages, 14262 KiB  
Article
Phase Shift APOD and POD Control Technique in Multi-Level Inverters to Mitigate Total Harmonic Distortion
by Kalsoom Bano, Ghulam Abbas, Mohammed Hatatah, Ezzeddine Touti, Ahmed Emara and Paolo Mercorelli
Mathematics 2024, 12(5), 656; https://doi.org/10.3390/math12050656 - 23 Feb 2024
Cited by 4 | Viewed by 1184
Abstract
Multi-level inverters are widely employed to generate new energy because of their huge capacity and benefits in sound control performance. One of the critical areas of study for multi-level inverters is control strategy research. In this study, the control strategy for a multi-level [...] Read more.
Multi-level inverters are widely employed to generate new energy because of their huge capacity and benefits in sound control performance. One of the critical areas of study for multi-level inverters is control strategy research. In this study, the control strategy for a multi-level inverter—which is frequently employed in HVDC and FACTS systems—is designed. An asymmetrical D.C. voltage source is supplied to create the appropriate output voltage waveform with fewer total harmonic distortions (THDs) at the output voltage and current waveforms. In this work, the pulse width modulation techniques of POD (phase opposition disposition) and APOD (alternative phase opposition disposition) MC PWM are applied to a multi-level inverter to generate the seven-level output voltage waveform. This study presents an enhanced variable carrier frequency APOD control approach that can successfully lower the overall harmonic distortion rate. The design and completion of the phase-shifting POD and APOD control strategies are followed by an analysis and comparison of the THD situation under various switching frequencies and a simulation and verification of the control strategy using MATLAB simulation. The TI DSP-based control approach has been programmed. The APOD technique increases the output voltage’s THD to 18.27%, while the output current waveform’s THD is reduced to 15.67% by utilizing the APOD PWM technique. Using the POD PWM approach increases the total harmonic distortion (THD) of the voltage waveform by 18.06% and the output current waveform’s THD by 15.45%. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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29 pages, 5953 KiB  
Article
Analysis of Transmission System Stability with Distribution Generation Supplying Induction Motor Loads
by Minal S. Salunke, Ramesh S. Karnik, Angadi B. Raju and Vinayak N. Gaitonde
Mathematics 2024, 12(1), 148; https://doi.org/10.3390/math12010148 - 2 Jan 2024
Viewed by 1038
Abstract
A distributed-power-generating source (DPGS) is intended to locally supply the increased power demand at a load bus. When applied in small amounts, a DPGS offers many technical and economic benefits. However, with large DPGS penetrations, the stability of the transmission system becomes a [...] Read more.
A distributed-power-generating source (DPGS) is intended to locally supply the increased power demand at a load bus. When applied in small amounts, a DPGS offers many technical and economic benefits. However, with large DPGS penetrations, the stability of the transmission system becomes a significant issue. This paper investigates the stability of a transmission system equipped with a DPGS at load centres supplying power to both a constant power (CP) and induction motor (IM) load. The DPGSs considered in the present study are microturbine and diesel turbine power generators (MTGS and DTGS), both interfaced with synchronous generators. The influence of an IM load supplied by the DPGS on small-signal stability is studied by a critical damping ratio analysis. On the other hand, time-domain indicators of the transient response following a short circuit are employed in the analysis. Further, a variance analysis test (VAT) is performed to determine the contribution of IM and CP loads on the system stability. The study revealed that large penetration levels of IM loads significantly affect the stability and depend on the kind of DPGS technology used. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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25 pages, 5375 KiB  
Article
Index Matrix-Based Modeling and Simulation of Buck Converter
by Nikolay Hinov, Polya Gocheva and Valeri Gochev
Mathematics 2023, 11(23), 4756; https://doi.org/10.3390/math11234756 - 24 Nov 2023
Cited by 1 | Viewed by 1137
Abstract
The approach described in this paper handles the parameters and characteristics (analog and discrete ones) of a Buck DC-DC converter (in its power and control parts) in a common manner. The usage of probably complicated differential equations for discrete dynamical systems is avoided [...] Read more.
The approach described in this paper handles the parameters and characteristics (analog and discrete ones) of a Buck DC-DC converter (in its power and control parts) in a common manner. The usage of probably complicated differential equations for discrete dynamical systems is avoided by means of index matrix equations, which can be easily understood. Compared to classical matrix models, the proposed index matrix models are more descriptive and also smaller in size. Such functionality is widely applied by the authors, and a new operation is defined and used as well. The relevance of the proposed techniques in power electronics, because of switching topologies and a limited numbers of components, is argued. Respective examples of functioning modes of the considered converter, in which power circuits and controllers are modeled jointly, are given. Estimations of analog values are based on partly linear dependencies, which are shown to be adequate in first-order analyses. Specific expressions for a Buck DC-DC converter are presented. A model-solving technique and an exhaustive search on a parameter space are considered in detail and automated via well-formalized algorithms. Nested parameter intervals and verifications with normal probability distributions are used in an optimization procedure. The full agreement of implementation via MATLAB source code with results obtained via Simulink is demonstrated. The short simulation times of this software (compared to Simulink and a .NET desktop application developed by the authors) justify the search for optimal variants in a wide multi-dimensional space. A max–min procedure with 10,000 simulations in each verification step is presented. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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11 pages, 624 KiB  
Article
Design of Polynomial Observer-Based Control of Fractional-Order Power Systems
by Hamdi Gassara, Imen Iben Ammar, Abdellatif Ben Makhlouf, Lassaad Mchiri and Mohamed Rhaima
Mathematics 2023, 11(21), 4450; https://doi.org/10.3390/math11214450 - 27 Oct 2023
Cited by 2 | Viewed by 942
Abstract
This research addresses the problem of globally stabilizing a distinct category of fractional-order power systems (F-OP) by employing an observer-based methodology. To address the inherent nonlinearity in these systems, we leverage a Takagi–Sugeno (TS) fuzzy model. The practical stability of the proposed system [...] Read more.
This research addresses the problem of globally stabilizing a distinct category of fractional-order power systems (F-OP) by employing an observer-based methodology. To address the inherent nonlinearity in these systems, we leverage a Takagi–Sugeno (TS) fuzzy model. The practical stability of the proposed system is systematically established through the application of a sum-of-squares (SOS) approach. To demonstrate the robustness and effectiveness of our approach, we conduct simulations of the power system using SOSTOOLS v3.00. Our study contributes to advancing the understanding of F-OP and provides a practical framework for their global stabilization. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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21 pages, 8674 KiB  
Article
Determining Unintentional Island Threshold to Enhance the Reliability in an Electrical Distribution Grid
by Ahmed Amirul Arefin, Md. Siddikur Rahman, Molla Shahadat Hossain Lipu, Mahidur R. Sarker, Narinderjit Singh Sawaran Singh and Sheikh Tanzim Meraj
Mathematics 2023, 11(4), 886; https://doi.org/10.3390/math11040886 - 9 Feb 2023
Cited by 4 | Viewed by 1580
Abstract
Due to the significant number of distributed generators in the electric power system, islanding detection requirements are becoming an increasingly prominent aspect of the power system. The island detection system depends on accurate threshold determination since an incorrect threshold might result in a [...] Read more.
Due to the significant number of distributed generators in the electric power system, islanding detection requirements are becoming an increasingly prominent aspect of the power system. The island detection system depends on accurate threshold determination since an incorrect threshold might result in a hazardous situation. To evaluate the proposed method’s capacity to discriminate between different events, this study examined different unintentional islanding conditions such as under frequency and over frequency. The purpose of this study is to establish the threshold of the under and over frequency island conditions. The under frequency island condition happens when the distributed generator (DG) capacity exceeds the amount of connected load; on the other hand, the over frequency island condition happens during a higher connected load compared to the capacity of the DG. The contribution of this research is to propose an unintentional island threshold setting technique based on bus voltage angle difference data of the phasor measurement unit (PMU). In the PowerWorld simulator, the Utility Kerteh (location: Terengganu, Malaysia) bus system has been designed and simulated in this work. The test system has four distinct islanding scenarios under two conditions, and the performance of the proposed methods demonstrates that for the under frequency islanding conditions the scenario’s threshold can be taken at a minimum of 40 milliseconds (ms) and a maximum of 60 ms, while the over frequency condition island threshold can be placed at a minimum of 60 ms and a maximum of 80 ms depending on the scenarios. Therefore, the proposed technique will be contributed to increase the reliability of the overall distribution grid so the unintentional island can be detected faster in terms of time. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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16 pages, 6405 KiB  
Article
Evaluation of the Fast Synchrophasors Estimation Algorithm Based on Physical Signals
by Mihail Senyuk, Khairan Rajab, Murodbek Safaraliev and Firuz Kamalov
Mathematics 2023, 11(2), 256; https://doi.org/10.3390/math11020256 - 4 Jan 2023
Cited by 3 | Viewed by 1642
Abstract
The goal of this study is to evaluate the performance of the fast algorithm for synchrophasor estimation proposed on the basis of a physical system. The test system is represented by a physical model of a power system with four synchronous generators (15 [...] Read more.
The goal of this study is to evaluate the performance of the fast algorithm for synchrophasor estimation proposed on the basis of a physical system. The test system is represented by a physical model of a power system with four synchronous generators (15 and 5 kVA). Three synchronous machines represent steam turbine generators, while the fourth machine represents a hydro generator. The proposed method of accuracy assessment is based on comparison of the original and the recovered signals, using values of amplitude and phase angle. The experiments conducted in the study include three-phase faults, two-phase faults and single-phase faults at various buses of the test model. Functional dependencies of initial signal standard deviation from the recovered signal are obtained, as well as those for sampling rate and window width. Based on the results, the following requirements for measurement system and window width are formulated: sampling rate of analog-to-digital converter should be 10 kHz; and window width should start from 5 ms. In addition, the fast algorithm of synchrophasor estimation was tested on event recorder signals. The sampling rate of these signals was 2 kHz. Acceptable window width for event recorder signals is 8 ms. The algorithm was implemented using programming language Python 3 for the testing purposes. The proposed fast algorithm of synchrophasor estimation can be applied in methods for emergency control and equipment state monitoring with short time response. Full article
(This article belongs to the Special Issue Modeling, Simulation, and Analysis of Electrical Power Systems)
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