Modern Power Systems and Units

Topic Information

Dear Colleagues,

The topics include a whole range of issues related to the generation of electricity and heat using fossil fuels, renewable energy sources and nuclear power. Municipal waste disposal and waste energy recovery in industry are also included. In particular, the papers will address the following topics:

1. fuels and energy sources
2. thermal energy
3. energy use,
4. economic, ecological, social and legal aspects of energy conversion.

The design, construction and operation of electricity and heat generation systems using renewable energy sources, nuclear energy and fossil fuels will be analysed. In view of the rapid development of renewable energy-based power generation, considerable attention will be given to the cooperation of existing large power units with distributed energy sources. Energy self-sufficient buildings using solar energy (photovoltaic cells, solar collectors) and air and ground source heat pumps are of particular importance to the utilisation of green technology in this field.

Modern heating, ventilating and air conditioning (HVAC) systems will also be among the focuses. New methods will be presented for the mathematical modelling of power and heat generation systems and equipment. Due to large fluctuations in the price of conventional fuels, a lot of attention will be paid to the development directions of power and heat generation systems, mainly with a view to price reduction and independence from a single supplier.

Prof. Dr. Jan Taler
Prof. Dr. Ali Cemal Benim
Prof. Dr. Sławomir Grądziel 
Dr. Marek Majdak
Prof. Dr. Moghtada Mobedi
Prof. Dr. Tomasz Sobota
Prof. Dr. Dawid Taler
Prof. Dr. Bohdan Węglowski
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Computation computation	1.9	3.5	2013	18.6 Days	CHF 1800	Submit
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400	Submit
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600	Submit
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600	Submit
Sustainability sustainability	3.3	6.8	2009	19.7 Days	CHF 2400	Submit
World Electric Vehicle Journal wevj	2.6	4.5	2007	16.2 Days	CHF 1400	Submit

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Published Papers (7 papers)

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All Computation Electronics Energies Sensors Sustainability WEVJ

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20 pages, 16784 KiB  

Open AccessArticle

Analysis of the Mechanical Stability of Power Transformer Windings Considering the Influence of Temperature Field

by Junxin Chen, Zhanlong Zhang, Zhihao Gao and Jinbo Wu

Energies 2025, 18(6), 1374; https://doi.org/10.3390/en18061374 - 11 Mar 2025

Viewed by 430

Abstract

The power transformer is a critical primary device in the power grid, and the verification of its winding mechanical stability is of paramount importance in ensuring the safe and stable operation of the power grid. In the conventional numerical calculation methods for verifying [...] Read more.

The power transformer is a critical primary device in the power grid, and the verification of its winding mechanical stability is of paramount importance in ensuring the safe and stable operation of the power grid. In the conventional numerical calculation methods for verifying the mechanical stability of power transformer windings, the influence of temperature variations at the winding hot spots on winding mechanical stability has not been taken into account. In reality, factors such as the transformer’s operating load rate, ambient temperature, and the duration of short-circuit fault currents passing through will affect the mechanical stability margin of the transformer windings. Under conditions such as winding aging, deformation, or other reasons, the transformer windings may become unstable due to material parameter degradation, leading to insufficient mechanical stability margin. This paper analyzes the mechanical stability of power transformer windings considering the impact of the temperature field. Initially, a numerical model for calculating short-circuit currents in transformers was established to compute the short-circuit current under three-phase short-circuit-to-ground conditions as an excitation. Subsequently, a 3D electromagnetic force finite element calculation model was developed to determine the electromagnetic forces experienced under this condition. The results of the calculated electromagnetic forces were then used in a numerical calculation method to assess the mechanical stability of the windings. Furthermore, a 3D transformer electromagnetic–thermal flow finite element model was created to calculate the steady-state temperature rise under various operating conditions of the transformer. This model is validated through transformer temperature rise tests, and transient temperature rises under different operating conditions are calculated. The obtained data are fitted using the nonlinear least squares method to derive a fitting function for the winding hot spot temperature concerning load rate, ambient temperature, and short-circuit time. Taking into consideration the influence of temperature on the yield strength and modulus of elasticity of transformer winding materials, the variation in mechanical stability margin of transformer windings due to temperature effects is analyzed. Additionally, the operating domain for preventing the transformer from becoming unstable under three-phase short-circuit impacts is calculated for different degrees of material parameter degradation. This method provides an effective reference for transformer design and operation, demonstrating clear practical value. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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18 pages, 4051 KiB  

Open AccessArticle

Robust Emergency Frequency Control with Wind Turbines via Decoupling Security Constraints and Modeling Uncertainties

by Guanghu Xu, Shuaishuai Feng, Deping Ke, Huanhuan Yang, Siyang Liao and Jian Xu

Sustainability 2025, 17(5), 1892; https://doi.org/10.3390/su17051892 - 23 Feb 2025

Viewed by 363

Abstract

In this paper, controllable wind turbines are employed for emergency frequency control to reduce cost. However, controllable wind turbines introduce significant modeling uncertainties in the form of uncertain environmental factors and model aggregation into the system. To pre-generate feasible emergency control strategies at [...] Read more.

In this paper, controllable wind turbines are employed for emergency frequency control to reduce cost. However, controllable wind turbines introduce significant modeling uncertainties in the form of uncertain environmental factors and model aggregation into the system. To pre-generate feasible emergency control strategies at the lowest cost, a robust optimization model is constructed for a potentially serious fault in power systems, which is a mixed-integer nonlinear robust programming issue with non-analytical calculation (for post-event system frequency). Therefore, this study proposes to first quantify the impact of modeling uncertainties on wind turbine regulation and find the most unfavorable uncertain scenarios for emergency frequency control. Then, based on the above-filtered scenarios, the original problem is transformed into mixed-integer nonlinear programming. A novel simplified algorithm is proposed to solve the above problem efficiently. Finally, a case study is conducted on a real regional power system. It is proved effective in reducing costs by regulating wind turbines for emergency control, and the proposed method is effective in dealing with the impact of modeling uncertainties. Also, high solving efficiency (12 s in case study) meets the demand for efficient online pre-decision-making for emergency control. The research is meaningful in the promotion of secure access to power systems for sustainable power. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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17 pages, 10625 KiB  

Open AccessArticle

A Predictive Model for Voltage Transformer Ratio Error Considering Load Variations

by Zhenhua Li, Jiuxi Cui, Paulo R. F. Rocha, Ahmed Abu-Siada, Hongbin Li and Li Qiu

World Electr. Veh. J. 2024, 15(6), 269; https://doi.org/10.3390/wevj15060269 - 19 Jun 2024

Viewed by 1384

Abstract

The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions. The integration of a substantial number of electric vehicles (EVs) and their charging infrastructures into the grid poses new challenges [...] Read more.

The accuracy of voltage transformer (VT) measurements is imperative for the security and reliability of power systems and the equitability of energy transactions. The integration of a substantial number of electric vehicles (EVs) and their charging infrastructures into the grid poses new challenges for VT measurement fidelity, including voltage instabilities and harmonic disruptions. This paper introduces an innovative transformer measurement error prediction model that synthesizes Multivariate Variational Mode Decomposition (MVMD) with a deep learning framework integrating Bidirectional Temporal Convolutional Network and Multi-Head Attention mechanism (BiTCN-MHA). The paper is aimed at enhancing VT measurement accuracy under fluctuating load conditions. Initially, the optimization of parameter selection within the MVMD algorithm enhances the accuracy and interpretability of bi-channel signal decomposition. Subsequently, the model applies the Spearman rank correlation coefficient to extract dominant modal components from both the decomposed load and original ratio error sequences to form the basis for input signal channels in the BiTCN-MHA model. By superimposing predictive components, an effective prediction of future VT measurement error trends can be achieved. This comprehensive approach, accounting for input load correlations and temporal dynamics, facilitates robust predictions of future VT measurement error trends. Computational example analysis of empirical operational VT data shows that, compared to before decomposition, the proposed method reduces the Root-Mean-Square Error (RMSE) by 17.9% and the Mean Absolute Error (MAE) by 23.2%, confirming the method’s robustness and superiority in accurately forecasting VT measurement error trends. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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17 pages, 7176 KiB  

Open AccessArticle

Field Programmable Gate Array-Based Smart Switch to Avoid Inrush Current in PV Installations

by Gerardo de J. Martínez-Figueroa, Felipe Córcoles and Santiago Bogarra

Sensors 2024, 24(4), 1121; https://doi.org/10.3390/s24041121 - 8 Feb 2024

Cited by 1 | Viewed by 1289

Abstract

This paper introduces an FPGA-based implementation of a smart switch designed to avoid inrush currents occurring during the connection of single-phase transformers utilized in grid-connected photovoltaic (PV) systems. The magnitude of inrush currents is notably impacted by the residual flux within the transformer [...] Read more.

This paper introduces an FPGA-based implementation of a smart switch designed to avoid inrush currents occurring during the connection of single-phase transformers utilized in grid-connected photovoltaic (PV) systems. The magnitude of inrush currents is notably impacted by the residual flux within the transformer core and the precise moment of energization relative to the wave cycle. Alternative methods frequently hinge on intricate procedures to estimate residual flux. This challenge is adeptly circumvented by the innovative smart control system proposed herein, rendering it a cost-effective solution for grid-connected PV systems. The proposed solution for mitigating inrush current remains effective, even in the face of challenges with current and voltage sensors. This resilience arises from the system’s ability to learn and adapt by leveraging information acquired from the network. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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24 pages, 1255 KiB  

Open AccessArticle

The Efficacy of Multi-Period Long-Term Power Transmission Network Expansion Model with Penetration of Renewable Sources

by Gideon Ude Nnachi, Yskandar Hamam and Coneth Graham Richards

Computation 2023, 11(9), 179; https://doi.org/10.3390/computation11090179 - 7 Sep 2023

Cited by 2 | Viewed by 1524

Abstract

The electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialisation, population growth, urbanisation and, of course, the evolution of modern technologies in this 4th industrial revolution era. Such a rapid increase in energy demand introduces a huge [...] Read more.

The electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialisation, population growth, urbanisation and, of course, the evolution of modern technologies in this 4th industrial revolution era. Such a rapid increase in energy demand introduces a huge challenge into the power system, which has paved way for network operators to seek alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such an increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a DC TNEP model that minimises the capital costs of additional transmission lines, network reinforcements, generator operation costs and the costs of renewable energy penetration, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model was tested in several IEEE test systems in multi-period scenarios. We also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variable decomposition techniques. Moreover, we intend to provide additional recommendations in terms of in which particular year (within a 20 year planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. This is achieved by running incremental period simulations from the base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time, even for large power grid system. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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16 pages, 6470 KiB  

Open AccessArticle

Decision Support Tool for Electric Power Generation Development: A Feasibility Analysis for a Nigerian Case

by Justicia Otobo, Rusdy Hartungi, Yusuf Ibraheem and Abouzar Estebsari

Electronics 2023, 12(13), 2807; https://doi.org/10.3390/electronics12132807 - 25 Jun 2023

Viewed by 1198

Abstract

Electricity is a crucial component of sustainable development in developing countries, providing opportunities to supply low-cost clean energy to their populations. This paper presents a decision support tool for the Nigerian case, allowing users to rank different enhancement options to meet future scenarios. [...] Read more.

Electricity is a crucial component of sustainable development in developing countries, providing opportunities to supply low-cost clean energy to their populations. This paper presents a decision support tool for the Nigerian case, allowing users to rank different enhancement options to meet future scenarios. The tool enables feasibility checks on infrastructure capacity and can handle various generation options, including low-cost renewable resources. It is easy to use for non-experts and decision-makers and incorporates an optimal power flow algorithm to minimize costs. Demonstrated on a modified IEEE 30-bus system informed by Nigerian scenarios, this tool can provide policymakers with valuable insights for long-term investment decisions and facilitate the delivery of low-cost clean energy to developing countries. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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18 pages, 3488 KiB  

Open AccessArticle

Research on Parameter Optimization Method of Sliding Mode Controller for the Grid-Connected Composite Device Based on IMFO Algorithm

by Ji Sun, Jiajun Liu, Miao Miao and Haokun Lin

Sensors 2023, 23(1), 149; https://doi.org/10.3390/s23010149 - 23 Dec 2022

Cited by 1 | Viewed by 1862

Abstract

In order to make the grid-connected composite device (GCCD) controller meet the requirements of different operating modes and complex working conditions of power grid, this paper proposes to introduce sliding mode control (SMC) into GCCD controller. Firstly, the mathematical model of MMC converter [...] Read more.

In order to make the grid-connected composite device (GCCD) controller meet the requirements of different operating modes and complex working conditions of power grid, this paper proposes to introduce sliding mode control (SMC) into GCCD controller. Firstly, the mathematical model of MMC converter is established, and the sliding mode controller is designed based on the SMC principle. Then, aiming at the problems of complex controller structure and difficult parameter tuning in multiple modes of the GCCD, this paper proposes a controller parameter optimization method based on improved Month Flame optimization (IMFO) algorithm. This method improves the MFO algorithm by introducing good point set (GPS) initialization and Levy flight strategy, which accelerates the convergence speed of the algorithm while avoiding falling into local optimization, and realizes the optimization of converter controller parameters. Under a variety of standard test functions, the advantages of the proposed IMFO algorithm are verified by comparing it with the traditional algorithm. Finally, in order to realize the automatic tuning of control parameters, the Python–PSCAD joint simulation method is studied and implemented. Taking the comprehensive integral of time and absolute error (CITAE) index as the objective function, the parameters of the sliding mode controller are optimized. The simulation results show that the controller parameters optimized by the IMFO algorithm can make the GCCD have better dynamic performance. Full article

(This article belongs to the Topic Modern Power Systems and Units)

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