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Energies
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Modeling, Simulation and Optimization of Power Systems: 2nd Edition
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Modeling, Simulation and Optimization of Power Systems: 2nd Edition

A Special Issue of Energies (ISSN 1996-1073) belonging to the section "F1: Electrical Power System".

Deadline for manuscript submissions: 20 January 2027 | Viewed by 5157

Editors

Dr. Lin Zhu

E-Mail Website
Guest Editor
School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Interests: power system stability and control; power system modeling and simulation; DC/FACTS technology; new energy generation and grid connection
Special Issues, Collections and Topics in MDPI journals
Dr. Zhigang Wu

E-Mail Website
Guest Editor
School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Interests: power system modeling; numerical simulation technology and applications of complex network theory in power systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Power systems are complex and interconnected networks that facilitate the generation, transmission, and distribution of electrical energy. Modeling, simulation, and optimization are crucial tools for understanding and managing the complex behavior of power systems, as well as for designing more efficient and reliable power systems.

This Special Issue seeks to bring together researchers and practitioners from academia to present the latest advances in the modeling, simulation, and optimization of power systems.

We invite original research papers, review articles, and case studies on topics that include, but are not limited to, the following:

  • Power system modeling and simulation techniques.
  • Optimization methods for power system planning and operation.
  • Energy management systems and smart grid technologies.
  • Power system stability and control.
  • Power system protection and reliability.
  • Power electronics and renewable energy integration.
  • Power system dynamics and transient analysis.
  • Demand response and energy storage systems.
  • Cybersecurity in power systems.
  • Economic analysis of power system planning and operation.

Dr. Lin Zhu
Dr. Zhigang Wu
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • power system transient stability
  • model reduction
  • real-time simulator
  • nonlinear modeling
  • parameter identification
  • dynamic equivalent
  • data-driven

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Published Papers (5 papers)

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Research

28 pages, 3894 KB  
Article
Robust Load-Model Parameter Identification from Ambient Measurements Under Time-Varying Nominal Power
by Kazuhiro Kamata, Ryosuke Shikuma, Yu Fujimoto and Yasuhiro Hayashi
Energies 2026, 19(18), 4348; https://doi.org/10.3390/en19184348 - 14 Sep 2026
Abstract
As inverter-based renewable generation increases, load modeling from ambient measurements is important for power-system stability assessment. Under ambient conditions, voltage and frequency variations are small, whereas time-varying nominal power can substantially affect load-power variation. If nominal-power variation is not considered, it may be [...] Read more.
As inverter-based renewable generation increases, load modeling from ambient measurements is important for power-system stability assessment. Under ambient conditions, voltage and frequency variations are small, whereas time-varying nominal power can substantially affect load-power variation. If nominal-power variation is not considered, it may be misattributed to voltage- and frequency-dependent load responses, resulting in biased parameter estimates. Because this misattribution depends on the variations within each time window, single-window estimation may suffer reduced accuracy. This study proposes a method that models time-varying nominal power using an autoregressive moving-average model to separate nominal-power variation from voltage- and frequency-dependent load responses and aggregates validation errors across multiple time windows to reduce dependence on any specific window. Numerical simulations under two nominal-power variation levels were compared with single-window estimation and a previously proposed sensitivity-based window-selection method. When the maximum 100 s peak-to-peak nominal-power variation was 1.0% of the mean nominal power, the proposed method achieved an overall error of 0.100, 86% lower than the mean single-window error and 79% lower than the best sensitivity-based result. Additional analyses under modified identification and data-generation conditions showed that the proposed method generally maintained comparatively low identification errors, although accuracy varied with the conditions. Full article
(This article belongs to the Special Issue Modeling, Simulation and Optimization of Power Systems: 2nd Edition)
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20 pages, 2691 KB  
Article
Improved Load Frequency Control Design for Interconnected Power Systems
by Van Nguyen Ngoc Thanh, De Huynh Tan, Hoai Duong Minh and Van Van Huynh
Energies 2026, 19(3), 702; https://doi.org/10.3390/en19030702 - 29 Jan 2026
Cited by 2 | Viewed by 634
Abstract
Managing frequency stability in modern interconnected power systems is a critical challenge, particularly under continuous load variations and increasing system complexity. In response to these challenges, this study introduces an Improved Grey Wolf Optimizer (IGWO)-based Proportional–Integral–Derivative (PID) controller as a solution for effective [...] Read more.
Managing frequency stability in modern interconnected power systems is a critical challenge, particularly under continuous load variations and increasing system complexity. In response to these challenges, this study introduces an Improved Grey Wolf Optimizer (IGWO)-based Proportional–Integral–Derivative (PID) controller as a solution for effective Load Frequency Control (LFC). The proposed method is tested on interconnected power systems integrating thermal (reheat and non-reheat) and hydropower plants. The simulations focus on continuous load variation and nonlinearity cases, where the GRC block is added in the model to closely mimic real-world operating conditions. The findings demonstrate that the IGWO-PID controller outperforms by achieving faster stabilization, minimizing frequency deviations, and ensuring robust performance compared to the Particle Swarm Optimization (PSO) algorithm. These results highlight the controller’s adaptability and scalability, offering a reliable approach to maintaining stability and operational efficiency in interconnected power systems. Full article
(This article belongs to the Special Issue Modeling, Simulation and Optimization of Power Systems: 2nd Edition)
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23 pages, 1912 KB  
Article
The Mathematical Modelling of Nonlinear String Oscillations in an Isotropic Viscoelastic Medium Using the Example of a Long Power Line
by Andriy Chaban, Petro Pukach, Tomasz Perzyński, Andrzej Szafraniec, Vitaliy Levoniuk, Aleksander Dydycz and Szymon Arkanowicz
Energies 2025, 18(23), 6206; https://doi.org/10.3390/en18236206 - 26 Nov 2025
Viewed by 806
Abstract
In this study, a nonlinear mathematical model of a thin string oscillating in an isotropic viscoelastic medium is developed. The model addresses external and internal mechanical energy dissipation in the string using components described by nonlinear exponential functions. The differential state equation of [...] Read more.
In this study, a nonlinear mathematical model of a thin string oscillating in an isotropic viscoelastic medium is developed. The model addresses external and internal mechanical energy dissipation in the string using components described by nonlinear exponential functions. The differential state equation of the studied item is based on a modified Hamilton–Ostrogradsky integral variation principle. The principle is modified by expanding the Lagrangian with two additional components: one addressing the external and internal mechanical energy dissipation in a system and the other addressing the energy of external non-potential forces acting on a system. To substantiate the existence and uniqueness of the solution to a mixed initial boundary problem, the general theory of nonlinear differential equations is applied. A long, single power line is used as an example; its elements oscillate between two support points of the wire. The computer simulation results for the nonlinear vibrations of the object are presented and analysed. Full article
(This article belongs to the Special Issue Modeling, Simulation and Optimization of Power Systems: 2nd Edition)
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23 pages, 3443 KB  
Article
Scheme of Dynamic Equivalence for Regional Power Grid Considering Multiple Feature Constraints: A Case Study of Back-to-Back VSC-HVDC-Connected Regional Power Grid in Eastern Guangdong
by Yuxuan Zou, Lin Zhu, Zhiwei Liang, Yonghao Hu, Shuaishuai Chen and Haichuan Zhang
Energies 2025, 18(23), 6145; https://doi.org/10.3390/en18236145 - 24 Nov 2025
Cited by 1 | Viewed by 861
Abstract
As the global energy system accelerates its transition towards high penetration of renewable energy and high penetration of power electronic devices, regional power grids have undergone profound changes in their structural forms and component composition compared to traditional power grids. Conventional dynamic equivalencing [...] Read more.
As the global energy system accelerates its transition towards high penetration of renewable energy and high penetration of power electronic devices, regional power grids have undergone profound changes in their structural forms and component composition compared to traditional power grids. Conventional dynamic equivalencing methods struggle to balance modeling accuracy and computational efficiency simultaneously. To address this challenge, this paper focuses on the dynamic equivalencing of regional power grids and proposes a dynamic equivalencing scheme considering multiple feature constraints. First, based on the structural characteristics and the evolution of dynamic attributes of regional power grids, three key constraint conditions are identified: network topology, spatial characteristics of frequency response, and nodal residual voltage levels. Secondly, a comprehensive equivalencing scheme integrating multiple constraints is designed, which specifically includes delineating the retained region through multi-objective optimization, optimizing the internal system based on coherent aggregation and the current sinks reduction (CSR) method, and constructing a grey-box external equivalent model composed of synchronous generators and composite loads to accurately fit the electrical characteristics of the external power grid. Finally, the proposed methodology is validated on a Back-to-Back VSC-HVDC-connected regional power grid in Eastern Guangdong, China. Results demonstrate that the equivalent system reproduces the original power-flow profile and short-circuit capacity with negligible deviation, while its transient signatures under both AC and DC faults exhibit high consistency with those of the reference system. Full article
(This article belongs to the Special Issue Modeling, Simulation and Optimization of Power Systems: 2nd Edition)
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18 pages, 5127 KB  
Article
Design of Two-Degree-of-Freedom PID Controllers Optimized by Bee Algorithm for Frequency Control in Renewable Energy Systems
by Sarawoot Boonkirdram, Sitthisak Audomsi, Worawat Sa-Ngiamvibool and Wassana Kasemsin
Energies 2025, 18(18), 4880; https://doi.org/10.3390/en18184880 - 13 Sep 2025
Cited by 3 | Viewed by 2144
Abstract
The increasing incorporation of renewable energy sources, such as photovoltaic and wind power, results in considerable variability and uncertainty within modern power systems, thereby complicating load frequency control. Conventional controllers, including PI and PID, often fail to provide sufficient performance in dynamic conditions. [...] Read more.
The increasing incorporation of renewable energy sources, such as photovoltaic and wind power, results in considerable variability and uncertainty within modern power systems, thereby complicating load frequency control. Conventional controllers, including PI and PID, often fail to provide sufficient performance in dynamic conditions. This study introduces a Two-Degree-of-Freedom PID (2DOF-PID) controller optimized through the Bee Algorithm (BA) for Load Frequency Control (LFC) in a two-area interconnected power system that includes renewable energy sources. The BA is employed to enhance controller parameters according to two objective functions: the Integral of Time-weighted Absolute Error (ITAE) and the Integral of Time-weighted Squared Error (ITSE). Simulation studies utilizing MATLAB/Simulink are conducted to evaluate the comparative effectiveness of PI, PID, and 2DOF-PID controllers. The results demonstrate that the 2DOF-PID controller consistently outperforms conventional PI and PID controllers in terms of frequency stability. The ITAE optimization of the 2DOF-PID results in a reduction in the ITAE index by more than 95% compared to PI and PID controllers, a decrease in settling time by approximately 40–60%, and a near elimination of overshoot and undershoot. Through ITSE optimization, the 2DOF-PID achieves an error reduction exceeding 90% and ensures smooth convergence with minimal oscillations. The PID controller has slightly improved effectiveness in minimizing tie-line power deviation, whereas the 2DOF-PID demonstrates greater resilience and damping capability in frequency regulation across both regions. The findings confirm that the Bee Algorithm-tuned 2DOF-PID controller serves as a robust and effective approach for frequency management in systems primarily reliant on renewable energy sources. Future research should incorporate multi-objective optimization algorithms that concurrently address frequency and tie-line power variations, thereby providing a more equitable control framework for practical Automatic Generation Control (AGC) operations. Full article
(This article belongs to the Special Issue Modeling, Simulation and Optimization of Power Systems: 2nd Edition)
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