Topic Editors

Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Prof. Dr. Zhijian Liu
Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Prof. Dr. Lin Jiang
Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK

Advances in Power Science and Technology

Abstract submission deadline
closed (29 February 2024)
Manuscript submission deadline
closed (31 May 2024)
Viewed by
18027

Topic Information

Dear Colleagues,

With the continuous increase in renewable energy in the power system, technologies such as grid control and optimization, energy storage planning, and wind power forecasting have become increasingly important. These technologies can help to realize the sustainable development of the power system and improve the security, stability, and reliability of the power grid.

The purpose of power grid control and optimization is to ensure the stability and reliability of the power system through real-time monitoring and adjust the operation of the power grid. The purpose of energy storage planning is to optimize the energy storage capacity and distribution of the power system to meet the load demand and respond to emergencies. The purpose of wind power prediction is to predict the future wind speed and wind energy using meteorology, statistics, and machine learning methods, so as to optimize the planning and scheduling of wind power generation.

The research of this topic involves many fields, including power system, energy storage technology, meteorology, statistics, and machine learning. Through relevant research, the challenges faced by the power system can be effectively solved and the sustainable development of the power industry can be promoted.

Prof. Dr. Bo Yang
Prof. Dr. Zhijian Liu
Prof. Dr. Lin Jiang
Topic Editors

Keywords

  • control
  • optimization
  • forecast
  • plan
  • power system

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Electricity
electricity
- 4.8 2020 20.3 Days CHF 1000
Electronics
electronics
2.9 5.3 2012 15.6 Days CHF 2400
Energies
energies
3.2 6.2 2008 16.1 Days CHF 2600
Processes
processes
3.5 5.1 2013 13.7 Days CHF 2400
Sustainability
sustainability
3.9 6.8 2009 18.8 Days CHF 2400

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Published Papers (20 papers)

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21 pages, 6811 KiB  
Article
Modeling and Suppression of Conducted Interference in Flyback Power Supplies Based on GaN Devices
by Jichi Yan, Haoyuan Wu, Xueliang Fu, Mingtong Li and Yannan Yu
Electronics 2024, 13(12), 2360; https://doi.org/10.3390/electronics13122360 - 16 Jun 2024
Viewed by 339
Abstract
The application of GaN power devices has significantly increased the power density of flyback power supplies but has also caused severe electromagnetic interference (EMI) issues. To address the challenge of conducted interference in flyback power supplies, a comprehensive analysis of the transmission mechanism [...] Read more.
The application of GaN power devices has significantly increased the power density of flyback power supplies but has also caused severe electromagnetic interference (EMI) issues. To address the challenge of conducted interference in flyback power supplies, a comprehensive analysis of the transmission mechanism of conducted common-mode noise is undertaken. This analysis involves simplifying the equivalent model of conducted interference and leveraging the circuit characteristics of conducted noise to propose a solution for attenuating common-mode noise. Considering the constraints of external compensation capacitors, a balanced winding is further introduced to mitigate the impact of noise. To enhance the efficacy of conducted interference suppression, it is suggested to change the winding structure of the transformer and incorporate a shielding winding. This configuration aims to minimize the generation and propagation of common-mode noise within the transformer. Finally, experimental verification is carried out using a 150 W GaN flyback power supply prototype. The experimental results demonstrate that the proposed method effectively suppresses common-mode noise in the circuit. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
15 pages, 7440 KiB  
Article
Exploring Motion Stability of a Novel Semi-Submersible Platform for Offshore Wind Turbines
by Hongxu Zhao, Xiang Wu and Zhou Zhou
Energies 2024, 17(10), 2313; https://doi.org/10.3390/en17102313 - 10 May 2024
Viewed by 590
Abstract
The stability of offshore floating wind turbine foundation platforms is a fundamental requirement for the efficiency and safety of wind power generation systems. This paper proposes a novel small-diameter float-type semi-submersible platform to improve system stability. To evaluate the superior motion stability of [...] Read more.
The stability of offshore floating wind turbine foundation platforms is a fundamental requirement for the efficiency and safety of wind power generation systems. This paper proposes a novel small-diameter float-type semi-submersible platform to improve system stability. To evaluate the superior motion stability of the proposed floating platform, a comprehensive frequency–domain response analysis and experimental study were conducted in comparison with the OC4-DeepCwind platform developed by the National Renewable Energy Laboratory (NREL). The respective comparison of the frequency–domain response analysis and the experimental results demonstrated that the proposed floating wind turbine platform shows better hydrodynamic characteristics and resonance avoidance capability. This not only reduces the Response Amplitude Operators (RAOs), but also enhances the system stability, namely, effectively avoiding the regions of concentrated wave loading and low-frequency ranges. Furthermore, the proposed small-diameter semi-submersible platform has the potential to reduce manufacturing costs, providing valuable insights for the manufacturing of offshore floating wind turbine systems. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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25 pages, 3600 KiB  
Article
A Novel Improved Variational Mode Decomposition-Temporal Convolutional Network-Gated Recurrent Unit with Multi-Head Attention Mechanism for Enhanced Photovoltaic Power Forecasting
by Hua Fu, Junnan Zhang and Sen Xie
Electronics 2024, 13(10), 1837; https://doi.org/10.3390/electronics13101837 - 9 May 2024
Viewed by 593
Abstract
Photovoltaic (PV) power forecasting plays a crucial role in optimizing renewable energy integration into the grid, necessitating accurate predictions to mitigate the inherent variability of solar energy generation. We propose a novel forecasting model that combines improved variational mode decomposition (IVMD) with the [...] Read more.
Photovoltaic (PV) power forecasting plays a crucial role in optimizing renewable energy integration into the grid, necessitating accurate predictions to mitigate the inherent variability of solar energy generation. We propose a novel forecasting model that combines improved variational mode decomposition (IVMD) with the temporal convolutional network-gated recurrent unit (TCN-GRU) architecture, enriched with a multi-head attention mechanism. By focusing on four key environmental factors influencing PV output, the proposed IVMD-TCN-GRU framework targets a significant research gap in renewable energy forecasting methodologies. Initially, leveraging the sparrow search algorithm (SSA), we optimize the parameters of VMD, including the mode component K-value and penalty factor, based on the minimum envelope entropy principle. The optimized VMD then decomposes PV power, while the TCN-GRU model harnesses TCN’s proficiency in learning local temporal features and GRU’s capability in rapidly modeling sequence data, while leveraging multi-head attention to better utilize the global correlation information within sequence data. Through this design, the model adeptly captures the correlations within time series data, demonstrating superior performance in prediction tasks. Subsequently, the SSA is employed to optimize GRU parameters, and the decomposed PV power mode components and environmental feature attributes are inputted into the TCN-GRU neural network. This facilitates dynamic temporal modeling of multivariate feature sequences. Finally, the predicted values of each component are summed to realize PV power forecasting. Validation using real data from a PV station corroborates that the novel model demonstrates a substantial reduction in RMSE and MAE of up to 55.1% and 54.5%, respectively, particularly evident in instances of pronounced photovoltaic power fluctuations during inclement weather conditions. The proposed method exhibits marked improvements in accuracy compared to traditional PV power prediction methods, underscoring its significance in enhancing forecasting precision and ensuring the secure scheduling and stable operation of power systems. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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31 pages, 3994 KiB  
Article
Collaborative Optimization Scheduling of Multi-Microgrids Incorporating Hydrogen-Doped Natural Gas and P2G–CCS Coupling under Carbon Trading and Carbon Emission Constraints
by Yuzhe Zhao and Jingwen Chen
Energies 2024, 17(8), 1954; https://doi.org/10.3390/en17081954 - 19 Apr 2024
Viewed by 458
Abstract
In the context of “dual carbon”, restrictions on carbon emissions have attracted widespread attention from researchers. In order to solve the issue of the insufficient exploration of the synergistic emission reduction effects of various low-carbon policies and technologies applied to multiple microgrids, we [...] Read more.
In the context of “dual carbon”, restrictions on carbon emissions have attracted widespread attention from researchers. In order to solve the issue of the insufficient exploration of the synergistic emission reduction effects of various low-carbon policies and technologies applied to multiple microgrids, we propose a multi-microgrid electricity cooperation optimization scheduling strategy based on stepped carbon trading, a hydrogen-doped natural gas system and P2G–CCS coupled operation. Firstly, a multi-energy microgrid model is developed, coupled with hydrogen-doped natural gas system and P2G–CCS, and then carbon trading and a carbon emission restriction mechanism are introduced. Based on this, a model for multi-microgrid electricity cooperation is established. Secondly, design optimization strategies for solving the model are divided into the day-ahead stage and the intraday stage. In the day-ahead stage, an improved alternating direction multiplier method is used to distribute the model to minimize the cooperative costs of multiple microgrids. In the intraday stage, based on the day-ahead scheduling results, an intraday scheduling model is established and a rolling optimization strategy to adjust the output of microgrid equipment and energy purchases is adopted, which reduces the impact of uncertainties in new energy output and load forecasting and improves the economic and low-carbon operation of multiple microgrids. Setting up different scenarios for experimental validation demonstrates the effectiveness of the introduced low-carbon policies and technologies as well as the effectiveness of their synergistic interaction. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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16 pages, 10751 KiB  
Technical Note
An Intelligent Controller of LED Street Light Based on Discrete Devices
by Zhan Wang, Dehua Zhang, Jishen Li and Wei Zhang
Energies 2024, 17(8), 1838; https://doi.org/10.3390/en17081838 - 11 Apr 2024
Viewed by 614
Abstract
To combat global environmental deterioration and energy scarcities, it is crucial to implement energy-saving upgrades for urban road lighting. Comparatively, LEDs have emerged as an advanced and eco-friendly lighting option due to their low energy consumption, excellent performance, high color rendering index, and [...] Read more.
To combat global environmental deterioration and energy scarcities, it is crucial to implement energy-saving upgrades for urban road lighting. Comparatively, LEDs have emerged as an advanced and eco-friendly lighting option due to their low energy consumption, excellent performance, high color rendering index, and prolonged lifespan. By incorporating solar cell technology, a smart LED street light controller based on small-scale integrated circuits was developed to enable intelligent control for various lighting needs such as dimming, timing, automatic detection, and sound and light control. Through circuit simulations and experimental outcomes, it has been validated that the controller’s structure and performance parameters align with the design specifications. This design encompasses knowledge from diverse fields, including fundamentals of circuit and electronic technology, photovoltaic cell technology, power electronics, and sensor technology, showcasing robust engineering and practicality. Its utilization in the experimental course for second-year college students majoring in electrical engineering contributes to the grooming of professionals and expands the perspectives of future talents, enriching their application of knowledge and practical innovation capabilities. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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16 pages, 5316 KiB  
Article
Optimization Operation Strategy for Shared Energy Storage and Regional Integrated Energy Systems Based on Multi-Level Game
by Yulong Yang, Tao Chen, Han Yan, Jiaqi Wang, Zhongwen Yan and Weiyang Liu
Energies 2024, 17(7), 1770; https://doi.org/10.3390/en17071770 - 8 Apr 2024
Viewed by 598
Abstract
Regional Integrated Energy Systems (RIESs) and Shared Energy Storage Systems (SESSs) have significant advantages in improving energy utilization efficiency. However, establishing a coordinated optimization strategy between RIESs and SESSs is an urgent problem to be solved. This paper constructs an operational framework for [...] Read more.
Regional Integrated Energy Systems (RIESs) and Shared Energy Storage Systems (SESSs) have significant advantages in improving energy utilization efficiency. However, establishing a coordinated optimization strategy between RIESs and SESSs is an urgent problem to be solved. This paper constructs an operational framework for RIESs considering the participation of SESSs. It analyzes the game relationships between various entities based on the dual role of energy storage stations as both energy consumers and suppliers, and it establishes optimization models for each stakeholder. Finally, the improved Differential Evolution Algorithm (JADE) combined with the Gurobi solver is employed on the MATLAB 2021a platform to solve the cases, verifying that the proposed strategy can enhance the investment willingness of energy storage developers, balance the interests among the Integrated Energy Operator (IEO), Energy Storage Operator (ESO) and the user, and improve the overall economic efficiency of RIESs. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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22 pages, 9244 KiB  
Article
Control Strategies of Thrust Ripple Suppression for Electromagnetic Microgravity Facility
by Yuman Li, Wenbo Dong, Congmin Lv, Zhe Wang and Yongkang Zhang
Electronics 2024, 13(7), 1247; https://doi.org/10.3390/electronics13071247 - 27 Mar 2024
Viewed by 497
Abstract
This paper presents an innovative solution that is able to suppress the thrust ripple in a high-power asynchronous linear induction motor (LIM) used in a microgravity experiment facility electromagnetic launch (MEFEL) system. By addressing the crucial need for low levels of thrust ripple [...] Read more.
This paper presents an innovative solution that is able to suppress the thrust ripple in a high-power asynchronous linear induction motor (LIM) used in a microgravity experiment facility electromagnetic launch (MEFEL) system. By addressing the crucial need for low levels of thrust ripple in MEFEL applications, we propose a dynamic model-based adaptive controller (MAC) and an enhanced quasi-proportional-resonant (PR) controller. The MAC is designed to compensate for the inherent impedance asymmetry of the linear motor. The PR controller minimizes thrust ripple by eliminating harmonics within the current loop. A comparative analysis indicates that both MAC and PR control are effective in reducing harmonics, suppressing the thrust ripple, and maintaining system stability. Computer simulations show a noteworthy 75% reduction in the thrust ripple and a decrease in the negative current. Partial tests on the MEFEL device validate the practical efficacy of the proposed control methods, emphasizing the method’s ability to enhance the quality of microgravity in real-world scenarios significantly. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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22 pages, 3126 KiB  
Article
Interval State Estimation of Electricity-Gas Systems Considering Measurement Correlations
by Yan Huang and Lin Feng
Energies 2024, 17(3), 755; https://doi.org/10.3390/en17030755 - 5 Feb 2024
Viewed by 515
Abstract
The popularization of electricity-gas systems leads to increasing demand for state management of systems. However, the existence of neglected measurement correlations brings uncertainties to the electricity-gas systems state estimation. In this paper, an interval state estimation method that considers measurement correlations existing in [...] Read more.
The popularization of electricity-gas systems leads to increasing demand for state management of systems. However, the existence of neglected measurement correlations brings uncertainties to the electricity-gas systems state estimation. In this paper, an interval state estimation method that considers measurement correlations existing in the electricity-gas systems is presented. We derive the linear measurement model for the electricity-gas systems through Taylor series expansion and estimate the measurement variance-covariance matrix with measurement correlations. The system parameter matrix and the measurement variance-covariance matrix containing measurement correlations are combined into an interval, and the interval state matrix considering measurement correlations is constructed. Then, the linear equations for the state estimation interval considering measurement correlations are established based on the measurement containing correlations and interval state matrix; as a result, the electricity-gas system state estimation model containing measurement correlations is established. In addition, a method for determining the range of state estimation intervals is proposed. Numerical tests on an integrated electricity-gas system comprising a 10-node natural gas network and IEEE 30-bus system indicate that the proposed approach has more advantages over the UT+KO approach in computation accuracy and computation efficiency. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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15 pages, 3772 KiB  
Article
A Layered Parallel Equaliser Based on Flyback Transformer Multiplexed for Lithium-Ion Battery System
by Hongrui Liu, Xiangyang Wei, Junjie Ai and Xudong Yang
Energies 2024, 17(3), 754; https://doi.org/10.3390/en17030754 - 5 Feb 2024
Viewed by 602
Abstract
An effective equaliser is crucial for eliminating inconsistencies in the connected serial batteries and extending the life of the battery system. The current equalisers generally have the problems of low equalisation efficiency, slow equalisation speed, and complex switching control. A layered parallel equaliser [...] Read more.
An effective equaliser is crucial for eliminating inconsistencies in the connected serial batteries and extending the life of the battery system. The current equalisers generally have the problems of low equalisation efficiency, slow equalisation speed, and complex switching control. A layered parallel equaliser based on a flyback transformer multiplexed for a lithium-ion battery system is proposed. The equaliser employs both hierarchical and parallel equalisation techniques, allowing for simultaneous processing of multiple objectives. This enhances both the efficiency and speed of the equalisation process. The efficiency of equalisation can be further improved by implementing PWM control with deadband complement. Additionally, the flyback transformer serves as an energy storage component for both layers of the equalisation module, resulting in a significant reduction in the size and cost of the equaliser. The circuit topology of the equaliser is presented, and its operational principle, switching control, and equalisation control strategy are analysed in detail. Finally, an experimental platform consisting of six lithium-ion batteries is constructed, and equalisation experiments are conducted to verify the advantages of the proposed equaliser in terms of equalisation speed, efficiency, and cost. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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18 pages, 2182 KiB  
Article
Hierarchical Blocking Control for Mitigating Cascading Failures in Power Systems with Wind Power Integration
by Lun Cheng, Tao Wang, Yuhang Wu, Zeming Gao and Ning Ji
Energies 2024, 17(2), 442; https://doi.org/10.3390/en17020442 - 16 Jan 2024
Viewed by 575
Abstract
The increasing uncertainty of wind power brings greater challenges to the control for mitigation of cascading failures. In order to minimize the risk of cascading failures in large-scale wind power systems at a lower economic cost, a multi-stage blocking control model is proposed [...] Read more.
The increasing uncertainty of wind power brings greater challenges to the control for mitigation of cascading failures. In order to minimize the risk of cascading failures in large-scale wind power systems at a lower economic cost, a multi-stage blocking control model is proposed based on sensitivity analysis. Firstly, the propagation mechanism of cascading failures in power systems with wind power integration is analyzed, and the propagation path of such failures is predicted. Subsequently, sensitive lines that are prone to failure are identified using the power sensitivity matrix, taking into account the effects of blocking control on the propagation path. By constraining the power flow of these sensitive lines, a multi-stage blocking control model for the predicted cascading failure path is proposed with the objective of minimizing the control cost and cascading failure probability. Based on probabilistic optimal power flow calculations, the constraints related to wind power uncertainty are transformed into opportunity constraints. To validate the effectiveness of the proposed model, the IEEE 39-node system is used as an example, and the results show that the obtained control method is able to balance economy and safety. In addition, the control costs for the same initial failure are higher as the wind power penetration rates and confidence levels increase. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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18 pages, 3393 KiB  
Article
Key Technologies of Intelligent Question-Answering System for Power System Rules and Regulations Based on Improved BERTserini Algorithm
by Ming Gao, Mengshi Li, Tianyao Ji, Nanfang Wang, Guowu Lin and Qinghua Wu
Processes 2024, 12(1), 58; https://doi.org/10.3390/pr12010058 - 26 Dec 2023
Viewed by 786
Abstract
With the continuous breakthrough of natural language processing, the application of intelligent question-answering technology in electric power systems has attracted wide attention. However, at present, the traditional question-answering system has poor performance and is difficult to apply in engineering practice. This paper proposes [...] Read more.
With the continuous breakthrough of natural language processing, the application of intelligent question-answering technology in electric power systems has attracted wide attention. However, at present, the traditional question-answering system has poor performance and is difficult to apply in engineering practice. This paper proposes an improved BERTserini algorithm for the intelligent answering of electric power regulations based on a BERT model. The proposed algorithm is implemented in two stages. The first stage is the text-segmentation stage, where a multi-document long text preprocessing technique is utilized that accommodates the rules and regulations text, and then Anserini is used to extract paragraphs with high relevance to the given question. The second stage is the answer-generation and source-retrieval stage, where a two-step fine-tuning based on the Chinese BERT model is applied to generate precise answers based on given questions, while the information regarding documents, chapters, and page numbers of these answers are also output simultaneously. The algorithm proposed in this paper eliminates the necessity for the manual organization of professional question–answer pairs, thereby effectively reducing the manual labor cost compared to traditional question-answering systems. Additionally, this algorithm exhibits a higher degree of exact match rate and a faster response time for providing answers. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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16 pages, 6409 KiB  
Article
New Equipment for Determining Friction Parameters in External Conditions: Measurements for the Design
by Martin Zidek, Filip Vanek, Lucie Jezerska, Rostislav Prokes and Daniel Gelnar
Processes 2023, 11(12), 3348; https://doi.org/10.3390/pr11123348 - 1 Dec 2023
Viewed by 815
Abstract
Friction parameters such as the angle of internal friction and the external friction of soils (bulk materials) show the possibilities of further material use. These are, for example, possibilities for soil processing, handling, and storage. The determination of friction parameters is usually carried [...] Read more.
Friction parameters such as the angle of internal friction and the external friction of soils (bulk materials) show the possibilities of further material use. These are, for example, possibilities for soil processing, handling, and storage. The determination of friction parameters is usually carried out under laboratory conditions. For the possibility of determining the properties of soils outside the laboratory in terms of immediate material response, a laboratory prototype was developed. The main objective for its development was to determine the effect of the shape of the friction surface when “sliding” on the soil. This was achieved with the help of validation equipment designed to measure, test, and validate the processes of raking, material piling, material transfer and removal, and tool movement or sliding on or in a material. It was found that by using an appropriate speed and normal load, the Jenike method can be applied to determine the angle of external friction over a shorter distance with an error of about 6–7.5% from the values measured on a calibrated shear machine. The results also showed that the method can be applied to detect the shear stresses that arise when a tool is plunged into a material, and thus predict the possible increase in energy loss during the process. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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26 pages, 8500 KiB  
Article
Research on Optimal Scheduling of Multi-Energy Microgrid Based on Stackelberg Game
by Bo Li, Yang Li, Ming-Tong Li, Dan Guo, Xin Zhang, Bo Zhu, Pei-Ru Zhang and Li-Di Wang
Processes 2023, 11(10), 2820; https://doi.org/10.3390/pr11102820 - 24 Sep 2023
Viewed by 908
Abstract
In recent years, rapid industrialization has driven higher energy demand, depleting fossil-fuel reserves and causing excessive emissions. China’s “dual carbon” strategy aims to balance development and sustainability. This study optimizes microgrid efficiency with a tiered carbon-priced economy. A Stackelberg game establishes microgrid-user equilibrium, [...] Read more.
In recent years, rapid industrialization has driven higher energy demand, depleting fossil-fuel reserves and causing excessive emissions. China’s “dual carbon” strategy aims to balance development and sustainability. This study optimizes microgrid efficiency with a tiered carbon-priced economy. A Stackelberg game establishes microgrid-user equilibrium, solved iteratively with a multi-population algorithm (MPGA). Comparative analysis can be obtained without considering demand response scenarios, and the optimization cost of microgrid operation considering price-based demand response scenarios was reduced by 5%; that is 668.95 yuan. In addition, the cost of electricity purchase was decreased by 23.8%, or 778.6 yuan. The model promotes user-driven energy use, elevating economic and system benefits, and therefore, the scheduling expectation of “peak shaving and valley filling” is effectively realized. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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19 pages, 5238 KiB  
Article
Massive Multi-Source Joint Outbound and Benefit Distribution Model Based on Cooperative Game
by Wang He, Min Liu, Chaowen Zuo and Kai Wang
Energies 2023, 16(18), 6590; https://doi.org/10.3390/en16186590 - 13 Sep 2023
Cited by 2 | Viewed by 704
Abstract
In light of the challenges posed by the widespread distribution of new energy sources in China and their distance from load centers, the power system must effectively integrate both new energy and thermal power transmission. To address this issue, we propose a dynamic [...] Read more.
In light of the challenges posed by the widespread distribution of new energy sources in China and their distance from load centers, the power system must effectively integrate both new energy and thermal power transmission. To address this issue, we propose a dynamic coordinated scheduling model that combines wind, photovoltaic, and thermal power to optimize the profit of the energy complementary delivery system. Additionally, we present an improved ant lion optimization algorithm to investigate the coordinated scheduling and benefit distribution of these three power sources. This paper introduces a cooperative mode for benefit distribution and utilizes an enhanced Shapley value method to allocate the benefits of joint operation among the three parties. The distribution of benefits is based on the contribution of each party to the joint proceeds, considering the profit levels of joint outbound and independent outbound modes. Through our analysis, we demonstrate that the upgraded ant lion optimization algorithm facilitates finding the global optimal solution more effectively within the feasible zone. Furthermore, our suggested three-party combined scheduling model and profit-sharing approach are shown to be superior and feasible. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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30 pages, 11943 KiB  
Article
Generalized Regression Neural Network Based Meta-Heuristic Algorithms for Parameter Identification of Proton Exchange Membrane Fuel Cell
by Peng He, Xin Zhou, Mingqun Liu, Kewei Xu, Xian Meng and Bo Yang
Energies 2023, 16(14), 5290; https://doi.org/10.3390/en16145290 - 10 Jul 2023
Cited by 1 | Viewed by 849
Abstract
An accurate parameter extraction of the proton exchange membrane fuel cell (PEMFC) is crucial for establishing a reliable cell model, which is also of great significance for subsequent research on the PEMFC. However, because the parameter identification of the PEMFC is a nonlinear [...] Read more.
An accurate parameter extraction of the proton exchange membrane fuel cell (PEMFC) is crucial for establishing a reliable cell model, which is also of great significance for subsequent research on the PEMFC. However, because the parameter identification of the PEMFC is a nonlinear optimization problem with multiple variables, peaks, and a strong coupling, it is difficult to solve this problem using traditional numerical methods. Furthermore, because of insufficient current and voltage data measured by the PEMFC, the precision rate of cell parameter extraction is also very low. The study proposes a parameter extraction method using a generalized regression neural network (GRNN) and meta-heuristic algorithms (MhAs). First of all, a GRNN is used to de-noise and predict the data to solve the problems in the field of PEMFC, which include insufficient data and excessive noise data of the measured data. After that, six typical algorithms are used to extract the parameters of the PEMFC under three operating conditions, namely high temperature and low pressure (HTLP), medium temperature and medium pressure (MTMP), and low temperature and high pressure (LTHP). The last results demonstrate that the application of GRNN can prominently decrease the influence of data noise on parameter identification, and after data prediction, it can greatly enhance the precision rate and reliability of MhAs parameter identification, specifically, under HTLP conditions, the V-I fitting accuracy achieved 99.39%, the fitting accuracy was 99.07% on MTMP, and the fitting accuracy was 98.70%. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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17 pages, 13408 KiB  
Article
Vibration Scale Model of a Converter Transformer Based on the Finite Element and Similarity Principle and Its Preparation
by Hao Wang, Li Zhang, Youliang Sun and Liang Zou
Processes 2023, 11(7), 1969; https://doi.org/10.3390/pr11071969 - 29 Jun 2023
Cited by 1 | Viewed by 1088
Abstract
A similarity criterion suitable for studying the vibration characteristics of converter transformers is proposed based on comprehensive consideration of geometric dimensions, electric field, magnetic field, force field, sound field, and coupling field interface interactions. By comparing the magnetic field, stress, displacement, sound field [...] Read more.
A similarity criterion suitable for studying the vibration characteristics of converter transformers is proposed based on comprehensive consideration of geometric dimensions, electric field, magnetic field, force field, sound field, and coupling field interface interactions. By comparing the magnetic field, stress, displacement, sound field distribution, and vibration characteristics of the scale model of the converter transformer with the initial model, the reliability of the similarity criterion was determined. Based on the vibration similarity criterion of the converter transformer, a prototype of the proportional model was designed and manufactured, and vibration signals under no-load and load conditions were tested. These signals correspond to the vibration signals of the iron core and winding in the finite element model, respectively. Through comparative analysis, the reliability of the prototype and the vibration similarity model of the converter transformer has been proven, which can provide an accurate and effective laboratory research platform for in-depth research on the vibration and noise of the converter transformer and equipment protection. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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19 pages, 4087 KiB  
Article
Receding Galerkin Optimal Control with High-Order Sliding Mode Disturbance Observer for a Boiler-Turbine Unit
by Gang Zhao, Yuge Sun, Zhi-Gang Su and Yongsheng Hao
Sustainability 2023, 15(13), 10129; https://doi.org/10.3390/su151310129 - 26 Jun 2023
Cited by 2 | Viewed by 858
Abstract
The control of the boiler-turbine unit is important for its sustainable and robust operation in power plants, which faces great challenges due to the control unit’s serious nonlinearity, unmeasurable states, variable constraints, and unknown time-varying lumped disturbances. To address the above issues, this [...] Read more.
The control of the boiler-turbine unit is important for its sustainable and robust operation in power plants, which faces great challenges due to the control unit’s serious nonlinearity, unmeasurable states, variable constraints, and unknown time-varying lumped disturbances. To address the above issues, this paper proposes a receding Galerkin optimal controller with a high-order sliding mode disturbance observer in a composite scheme, in which a high-order sliding mode disturbance observer is first employed to estimate the lumped disturbances based on a deviation form of the mathematical model of the boiler-turbine unit. Subsequently, under the hypothesis of state constraint, a receding Galerkin optimal controller is designed to compensate the lumped disturbances by embedding their estimates into the mathematically based predictive model at each sampling time instant. With the help of an interpolation polynomial, Gauss integration, and nonlinear solvers, an optimal control law is then obtained based on a Galerkin optimization algorithm. Consequently, disturbance rejection, target tracking, and constraint handling performance of a controlled closed-loop system are improved. Some simulation cases are conducted on a mathematical boiler-turbine unit model to demonstrate the effectiveness of the proposed method, which is supported by the quantitative result analysis, such as tracking and disturbance rejection performance indexes. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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28 pages, 10095 KiB  
Article
Design of Intelligent Nonlinear H2/H Robust Control Strategy of Diesel Generator-Based CPSOGSA Optimization Algorithm
by Yidong Zou, Boyi Xiao, Jing Qian and Zhihuai Xiao
Processes 2023, 11(7), 1867; https://doi.org/10.3390/pr11071867 - 21 Jun 2023
Viewed by 1406
Abstract
In today’s human society, diesel generators (DGs) are widely applied in the human energy and electricity supply system due to its technical, operational, and economic advantages. This paper proposes an intelligent nonlinear H2/H robust controller based on the chaos [...] Read more.
In today’s human society, diesel generators (DGs) are widely applied in the human energy and electricity supply system due to its technical, operational, and economic advantages. This paper proposes an intelligent nonlinear H2/H robust controller based on the chaos particle swarm gravity search optimization algorithm (CPSOGSA), which controls the speed and excitation of a DG. In this method, firstly, establish the nonlinear mathematical model of the DG, and then design the nonlinear H2/H robust controller based on this. The direct feedback linearization and the H2/H robust control theory are combined and applied. Based on the design of the integrated controller for DG speed and excitation, the system’s performance requirements are transformed into a standard robust H2/H control problem. The parameters of the proposed solution controller are optimized by using the proposed CPSOGSA. The introduction of CPSOGSA completes the design of an intelligent nonlinear H2/H robust controller for DG. The simulation is implemented in MATLAB/Simulink, and the results are compared with the PID control method. The obtained results prove that the proposed method can effectively improve the dynamic accuracy of the system and the ability to suppress disturbances and improve the stability of the system. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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16 pages, 660 KiB  
Article
Optimizing Power Demand Side Response Strategy: A Study Based on Double Master–Slave Game Model of Multi-Objective Multi-Universe Optimization
by Diandian Hu and Tao Wang
Energies 2023, 16(10), 4009; https://doi.org/10.3390/en16104009 - 10 May 2023
Cited by 2 | Viewed by 1124
Abstract
In the pilot provinces of China’s electricity spot market, power generation companies usually adopt the separate bidding mode, which leads to a low willingness of demand-side response and poor flexibility in the interaction mechanism between supply and demand. Based on the analysis of [...] Read more.
In the pilot provinces of China’s electricity spot market, power generation companies usually adopt the separate bidding mode, which leads to a low willingness of demand-side response and poor flexibility in the interaction mechanism between supply and demand. Based on the analysis of the demand response mechanism of the power day-ahead market with the participation of power sales companies, this paper abstracted the game process of the “power grid-sales company-users” tripartite competition in the electricity market environment into a two-layer (purchase layer/sales layer) game model and proposed a master–slave game equilibrium optimization strategy for the day-ahead power market under the two-layer game. The multi-objective multi-universe optimization algorithm was used to find the Pareto optimal solution of the game model, a comprehensive evaluation was constructed, and the optimal strategy of the demand response was determined considering the peak cutting and valley filling quantity of the power grid, the profit of the electricity retailers, the cost of the consumers, and the comfort degree. Examples are given to simulate the day-ahead electricity market participated in by the electricity retailers, analyze and compare the benefits of each market entity participating in the demand response, and verify the effectiveness of the proposed model. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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19 pages, 3851 KiB  
Article
A Preventive Control Approach for Power System Vulnerability Assessment and Predictive Stability Evaluation
by Ersen Akdeniz and Mustafa Bagriyanik
Sustainability 2023, 15(8), 6691; https://doi.org/10.3390/su15086691 - 15 Apr 2023
Cited by 1 | Viewed by 1448
Abstract
Early detection of cascading failures phenomena is a vital process for the sustainable operation of power systems. Within the scope of this work, a preventive control approach implementing an algorithm for selecting critical contingencies by a dynamic vulnerability analysis and predictive stability evaluation [...] Read more.
Early detection of cascading failures phenomena is a vital process for the sustainable operation of power systems. Within the scope of this work, a preventive control approach implementing an algorithm for selecting critical contingencies by a dynamic vulnerability analysis and predictive stability evaluation is presented. The analysis was carried out using a decision tree with a multi-parameter knowledge base. After the occurrence of an initial contingency, probable future contingencies are foreseen according to several vulnerability perspectives created by an adaptive vulnerability search module. Then, for cases identified as critical, a secure operational system state is proposed through a vulnerability-based, security-constrained, optimal power flow algorithm. The modular structure of the proposed algorithm enables the evaluation of possible vulnerable scenarios and proposes a strategy to alleviate the technical and economic impacts due to prospective cascading failures. The presented optimization methodology was tested using the IEEE-39 bus test network and a benchmark was performed between the proposed approach and a time domain analysis software model (EMTP). The obtained results indicate the potential of analysis approach in evaluating low-risk but high-impact vulnerabilities in power systems. Full article
(This article belongs to the Topic Advances in Power Science and Technology)
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