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Power Systems Stability in Current and Future Scenarios
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Power Systems Stability in Current and Future Scenarios

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 6200

Special Issue Editor

Dr. Rossano Musca

E-Mail Website
Guest Editor
Dipartimento di Ingegneria, Università di Palermo, 90128 Palermo, Italy
Interests: renewable energy sources; dynamic analysis; grid integration; frequency control; system stability; modeling and algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The evolution of power systems poses several challenges in terms of their control and stability. Conventional approaches and analyses might no longer be valid under new scenarios, and therefore, further research, methodologies, and studies are certainly required. Some aspects, which are relevant in both current and future scenarios, include decrease in inertia and frequency stability issues; decrease in system strength and voltage stability issues; decrease in damping in the system and oscillatory stability issues; effects of the control of power converters, either grid-following or grid-forming.

This Special Issue invites original research papers and review articles addressing the different aspects of power systems dynamics, control, and stability in current and future scenarios.

Dr. Rossano Musca
Guest Editor

Manuscript Submission Information

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Keywords

  • power systems control
  • power systems stability
  • power systems dynamics
  • frequency stability
  • voltage stability
  • oscillatory stability
  • system inertia
  • system strength
  • system damping
  • power converters
  • grid-following
  • grid-forming

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Published Papers (3 papers)

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Research

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23 pages, 1153 KiB  
Article
A New Framework for Active Loss Reduction and Voltage Profile Enhancement in a Distributed Generation-Dominated Radial Distribution Network
by Adedayo Owosuhi, Yskandar Hamam and Josiah Munda
Appl. Sci. 2024, 14(3), 1077; https://doi.org/10.3390/app14031077 - 26 Jan 2024
Viewed by 850
Abstract
In recent times, a significant amount of power loss and system instability due to high voltage deviation experienced by modern power systems, in addition to the pressing issues challenging the power industry such as pollution—especially the emission of greenhouse gases—and aging infrastructures, have [...] Read more.
In recent times, a significant amount of power loss and system instability due to high voltage deviation experienced by modern power systems, in addition to the pressing issues challenging the power industry such as pollution—especially the emission of greenhouse gases—and aging infrastructures, have posed a serious threat to system operations. Distributed generation has been identified as one main solution capable of reducing pollution when solar and wind power are used and, hence, rejuvenating dilapidated infrastructures and redeeming climatic changes. This paper presents a novel two-stage approach for the identification of suitable locations for DG placement and the sizing of DG for loss reduction and voltage stability enhancement. The first stage explored the use of a network structure to develop a coupling factor (CF) approach that was non-iterative in nature to determine suitable DG locations. In the second stage, the size of the DG was determined using the particle swarm optimization (PSO) algorithm. The main objective was to obtain an optimal voltage profile of the system under consideration while lowering the power loss in the system and ensuring network stability amidst DG incorporation. The model design, optimization and simulation were carried out using the MATLAB 2016a environment and the IEEE 33-bus test system, in which DG was integrated. The influence of increasing the level of DG placement in the system was then investigated. The forward/backward sweep method was applied to monitor the optimization process. The voltage profiles for both the base case when no DG was integrated and the case of incremental DG integration were considered. The results obtained for both single and multiple DG integration are compared with those obtained using the existing methods. The results show the efficiency and applicability of the new non-iterative scheme in the quick identification of DG locations for voltage profile enhancement and network real power loss reduction in radial distribution networks. Full article
(This article belongs to the Special Issue Power Systems Stability in Current and Future Scenarios)
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18 pages, 4293 KiB  
Article
Development of Energy Storage Systems for High Penetration of Renewable Energy Grids
by Lun-Yi Lung, Tsan-Yu Chou, Wen-Ching Chang and Cheng-Chien Kuo
Appl. Sci. 2023, 13(21), 11978; https://doi.org/10.3390/app132111978 - 2 Nov 2023
Cited by 3 | Viewed by 1730
Abstract
As the proportion of renewable energy generation systems increases, traditional power generation facilities begin to face challenges, such as reduced output power and having the power turned off. The challenges are causing changes in the structure of the power system. Renewable energy sources, [...] Read more.
As the proportion of renewable energy generation systems increases, traditional power generation facilities begin to face challenges, such as reduced output power and having the power turned off. The challenges are causing changes in the structure of the power system. Renewable energy sources, mainly wind and solar energy cannot provide stable inertia and frequency regulation capability. Ultimately, the power system’s emergency response capability to face an N-1 is reduced, which leads to a reduction in system stability. Therefore, the application technology of the battery energy storage system is used to support the impact of changes in the new power system structure. This paper designed control technologies based on the WECC second-generation generic model, namely, dynamic regulation, steady regulation, and virtual inertia regulation. The models and control strategies are verified on Taiwan’s 2025 power system target conditions, which consider the expected capacities for battery energy storage systems, and renewable energy sources with different load and N-1 fault levels. According to the simulation results, the capabilities of the RoCoF limitation, frequency nadir, frequency recovery, and system oscillation regulation are evaluated in the proposed strategies. Finally, the analysis results can help power operators make informed decisions when selecting and deploying battery energy storage systems. Full article
(This article belongs to the Special Issue Power Systems Stability in Current and Future Scenarios)
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Review

Jump to: Research

39 pages, 3464 KiB  
Review
A Comprehensive Review on the Role of Artificial Intelligence in Power System Stability, Control, and Protection: Insights and Future Directions
by Ibrahim Alhamrouni, Nor Hidayah Abdul Kahar, Mohaned Salem, Mahmood Swadi, Younes Zahroui, Dheyaa Jasim Kadhim, Faisal A. Mohamed and Mohammad Alhuyi Nazari
Appl. Sci. 2024, 14(14), 6214; https://doi.org/10.3390/app14146214 - 17 Jul 2024
Cited by 2 | Viewed by 1790
Abstract
This review comprehensively examines the burgeoning field of intelligent techniques to enhance power systems’ stability, control, and protection. As global energy demands increase and renewable energy sources become more integrated, maintaining the stability and reliability of both conventional power systems and smart grids [...] Read more.
This review comprehensively examines the burgeoning field of intelligent techniques to enhance power systems’ stability, control, and protection. As global energy demands increase and renewable energy sources become more integrated, maintaining the stability and reliability of both conventional power systems and smart grids is crucial. Traditional methods are increasingly insufficient for handling today’s power grids’ complex, dynamic nature. This paper discusses the adoption of advanced intelligence methods, including artificial intelligence (AI), deep learning (DL), machine learning (ML), metaheuristic optimization algorithms, and other AI techniques such as fuzzy logic, reinforcement learning, and model predictive control to address these challenges. It underscores the critical importance of power system stability and the new challenges of integrating diverse energy sources. The paper reviews various intelligent methods used in power system analysis, emphasizing their roles in predictive maintenance, fault detection, real-time control, and monitoring. It details extensive research on the capabilities of AI and ML algorithms to enhance the precision and efficiency of protection systems, showing their effectiveness in accurately identifying and resolving faults. Additionally, it explores the potential of fuzzy logic in decision-making under uncertainty, reinforcement learning for dynamic stability control, and the integration of IoT and big data analytics for real-time system monitoring and optimization. Case studies from the literature are presented, offering valuable insights into practical applications. The review concludes by identifying current limitations and suggesting areas for future research, highlighting the need for more robust, flexible, and scalable intelligent systems in the power sector. This paper is a valuable resource for researchers, engineers, and policymakers, providing a detailed understanding of the current and future potential of intelligent techniques in power system stability, control, and protection. Full article
(This article belongs to the Special Issue Power Systems Stability in Current and Future Scenarios)
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