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Flow Control and Optimization in Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: 25 July 2025 | Viewed by 5337

Special Issue Editor

School of Power and Energy, Northwestern Polytechnical University, Xi'an, China
Interests: flow control and optimization; green aviation propulsion system

Special Issue Information

Dear Colleagues,

Power systems are broadly applied in aeronautics, aerospace sea, and land transportation, as well as in energy and chemical industries. Fluid organization and flow control technology in the power system can improve the performance, efficiency, and reliability. Therefore, this is a promising and attractive research area for both industry professionals and the academic community. In recent years, some advanced technology, e.g., additive manufacturing, artificial intelligence, and MEMS, have made flow control more efficient and feasible. Optimization through mathematical algorithms aims to search the best shape or strategies which can be within the generalized flow control.

This Special Issue aims to present and disseminate the most recent advances related to the theory, design, modelling, experiment, and application of all types of flow control in power systems.

Topics of interest for publication include, but are not limited to, the following:

  • Active flow control;
  • Passive flow control;
  • Hybrid control;
  • Intelligent control;
  • Drag reduction;
  • Noise reduction;
  • Optimization method;
  • Surrogate model;
  • Component  optimization;
  • Power system optimization;
  • Multidisciplinary optimization.

Dr. Hanru Liu
Guest Editor

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.

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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
  • flow control
  • optimization
  • modelling
  • experiment

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Published Papers (4 papers)

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Research

28 pages, 6291 KiB  
Article
Methodology for Optimal Design of Active Fluid Film Bearings Considering Their Power Losses, Stability and Controllability: Theory and Experiment
by Denis Shutin, Alexander Fetisov, Maksim Litovchenko, Aleksey Rodichev, Yuri Kazakov and Leonid Savin
Energies 2024, 17(23), 5879; https://doi.org/10.3390/en17235879 - 23 Nov 2024
Viewed by 1026
Abstract
This study addresses the problem of the automated synthesis of active fluid film bearings optimized for their adjustable design for new generations of turbomachines. The developed methodology proposes a criterion describing the ability of a bearing’s mechanical design to effectively implement control actions [...] Read more.
This study addresses the problem of the automated synthesis of active fluid film bearings optimized for their adjustable design for new generations of turbomachines. The developed methodology proposes a criterion describing the ability of a bearing’s mechanical design to effectively implement control actions along with its energy efficiency and stability properties considered in a solved multi-objective optimization problem. The design process of actively lubricated journal bearings was investigated in the context of the proposed approach. A multi-objective optimization problem was solved with heuristic algorithms. An analysis of the results obtained with the MOGA and MOPSO algorithm revealed their shortcomings emerging in such problems. The MOPSO algorithm was improved to expand the range and uniformity of the distribution of solutions in the resulting Pareto set and to speed up calculations. Four bearing configurations with significantly different properties were selected from the obtained set of solutions, manufactured and experimentally tested, showing the good agreement between the actual parameters and those set during the design procedure. The results substantiate the applicability of the proposed theoretical and computational tools for designing active fluid film bearings with pre-specified properties to meet the comprehensive requirements of the energy efficiency, reliability and service life of turbomachines. Full article
(This article belongs to the Special Issue Flow Control and Optimization in Power Systems)
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25 pages, 6729 KiB  
Article
A Novel Hybrid Harris Hawk Optimization–Sine Cosine Algorithm for Congestion Control in Power Transmission Network
by Vivek Kumar, R. Narendra Rao, Md Fahim Ansari, Vineet Shekher, Kaushik Paul, Pampa Sinha, Abdulaziz Alkuhayli, Usama Khaled and Mohamed Metwally Mahmoud
Energies 2024, 17(19), 4985; https://doi.org/10.3390/en17194985 - 5 Oct 2024
Viewed by 1208
Abstract
In a deregulated power system, managing congestion is crucial for effective operation and control. The goal of congestion management is to alleviate transmission line congestion while adhering to system constraints at minimal cost. This research proposes a hybrid Harris Hawk Optimization–Sine Cosine Algorithm [...] Read more.
In a deregulated power system, managing congestion is crucial for effective operation and control. The goal of congestion management is to alleviate transmission line congestion while adhering to system constraints at minimal cost. This research proposes a hybrid Harris Hawk Optimization–Sine Cosine Algorithm (hHHO-SCA) for an efficient generation rescheduling approach to achieve the lowest possible congestion cost. The hybridization has been performed by introducing the features of SCA in the HHO to boost the exploration and exploitation steps of HHO, providing an efficient global solution and effectively optimizing rescheduled power output. The effectiveness of this methodology is evaluated using IEEE 30 and IEEE 118-bus test systems, taking into account system parameters. The potency of the proposed method is analyzed by comparing the results of the hHHO-SCA with those from other recent optimization techniques. The findings show that the hHHO-SCA outperforms other methods by avoiding local optima and demonstrating promising convergence characteristics. Full article
(This article belongs to the Special Issue Flow Control and Optimization in Power Systems)
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15 pages, 4077 KiB  
Article
Decentralized Multi-Area Economic Dispatch in Power Systems Using the Consensus Algorithm
by Ying-Yi Hong and Hao Zeng
Energies 2024, 17(15), 3609; https://doi.org/10.3390/en17153609 - 23 Jul 2024
Cited by 2 | Viewed by 1029
Abstract
A multi-area power system requires coordination to enhance reliability and reduce operating costs. Economic dispatch in such systems is crucial because of the uncertainties associated with variable loads and the increasing penetration of renewable energy sources. This paper presents a hierarchical consensus algorithm [...] Read more.
A multi-area power system requires coordination to enhance reliability and reduce operating costs. Economic dispatch in such systems is crucial because of the uncertainties associated with variable loads and the increasing penetration of renewable energy sources. This paper presents a hierarchical consensus algorithm designed to determine the economic dispatch in a multi-area power system, accounting for the uncertainties in load and renewable generation. The proposed algorithm, which utilizes distributed agents, operates across three levels. Level 1 coordinates all areas, while levels 2 and 3 form a leader–follower consensus algorithm for overall economic dispatch. Breadth-first search is employed to identify the leader agent within each area. To address the uncertainties in loads and renewable generation, Monte Carlo simulations are performed. The efficacy of the proposed method is validated using the IEEE 39-bus and 118-bus systems, as well as a realistic 1968-bus power system in Taiwan. The traditional equal lambda method is employed to verify that the proposed approach is suitable for multi-area power systems using distributed computation. Full article
(This article belongs to the Special Issue Flow Control and Optimization in Power Systems)
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15 pages, 1439 KiB  
Article
Electrical Power Systems Reinforcement through Overall Contingency Index Analysis and Improvement
by Diego Romero, Diego Carrión and Manuel Jaramillo
Energies 2024, 17(11), 2506; https://doi.org/10.3390/en17112506 - 23 May 2024
Cited by 1 | Viewed by 1317
Abstract
This paper analyzes the behavior of an electrical power system when N-1 contingencies occur in the transmission stage, which can be produced by incorrect operation of the protection relays, phenomena of natural origin, or increased loadability, which affect the operation and reliability of [...] Read more.
This paper analyzes the behavior of an electrical power system when N-1 contingencies occur in the transmission stage, which can be produced by incorrect operation of the protection relays, phenomena of natural origin, or increased loadability, which affect the operation and reliability of the electrical system. The operation output of a transmission line results in the variation of the nominal values of the electrical parameters involved because they disturb the stability of the generation, transmission systems, and the supply of electrical energy to the loads, such as voltages and angles of the nodes and the active and reactive power of the system. The proposed methodology was based on analyzing the different electrical parameters of the power system, quantifying the contingency index in a state of regular operation, and comparing it to operation in contingency N-1, with which the most severe contingency was determined and, therefore, achieved; identifying contingencies that can cause system collapses; improving the contingency index from 23.08555 to 22.9276624 for the L16–19 contingency and to 22.9795235 for the L21–22 contingency, which are the most severe contingencies determined with the proposed methodology. To test the proposed methodology, the IEEE 39 bus-bar test system was considered, and the elements that should be implemented to avoid the vulnerability of the power system to N-1 contingencies were determined. Full article
(This article belongs to the Special Issue Flow Control and Optimization in Power Systems)
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