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Improving Power Response of Single-controllable VSG-Based Active Distribution Network

CSEE Journal of Power and Energy systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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System Optimal Routing and Distribution of Benefits on National Road Networks

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Transportation Research Procedia 2025年 82卷 2532-2545页

作者： Alexander Roocroft Giuliano Punzo Muhamad Azfar Ramli Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Institute of High Performance Computing A*STAR Singapore

Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rerouting through the empirical price of anarchy, a measure of network efficiency. However, studies using real-world measurements have been limited by methodological accuracy and network size. Also, they have lacked understanding of the spatial distribution of benefits from rerouting and the relationship with marginal external cost road charges that can be used for implementation. In this article, we create an accurate data-driven traffic assignment model of England's Strategic Road Network. We use it to calculate the national price of anarchy, which is found to be almost 1 implying gains from rerouting at the national scale are minimal and smaller than in other studies. The results show the distribution of rerouting benefits varies strongly with different network zones and demand profiles. This did not match the distribution of marginal external cost charges. Some zones have noticeable benefits from rerouting although the overall network benefit is small, however, these zones do not coincide with where the largest road charges have to be applied for system-optimal rerouting. These results have implications for rerouting implementation.

关键词： Strategic Road Network Empirical Price of Anarchy National Traffic Assignment

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Deterministic Learning-Based Tracking control for Parabolic PDE systems With Infinite-Dimensional Nonlinear Uncertain Dynamics

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IEEE Transactions on automatic control 2025年第5期70卷 3272-3287页

作者： Zhang, Jingting Yuan, Chengzhi Wu, Fen Wang, Cong Cheng, Hong University of Electronic Science and Technology of China Center for Robotics School of Automation Engineering Chengdu611731 China University of Rhode Island Mechanical Industrial and Systems Engineering Department KingstonRI02881 United States North Carolina State University Mechanical and Aerospace Engineering Department RaleighNC27695 United States Shandong University School of Control Science and Engineering Jinan250061 China

In this article, we investigate the joint problem of dynamics learning and tracking control for a class of parabolic partial differential equation (PDE) systems with infinite-dimensional uncertain nonlinear dynamics. A new learning control scheme is proposed based on the deterministic learning (DL) theory. One key feature of the proposed scheme is its capability of accurately learning the system's nonlinear uncertain dynamics during real-time tracking control with provable stability and convergence of the overall PDE closed-loop system. Specifically, the Galerkin method is first employed to deal with the infinite dimensionality of the PDE system;a novel DL-based adaptive learning control scheme is then proposed using dual radial basis function neural networks (RBF NNs), in which a pair of RBF NNs are employed to address, respectively, the matched and unmatched components of uncertain nonlinear system dynamics. This control scheme is finally examined on the original PDE system, and it is rigorously proved that: first the PDE system's state tracks the prescribed reference trajectory with guaranteed closed-loop stability and tracking accuracy;and second locally accurate identification of the PDE system's dominant nonlinear uncertain dynamics can be achieved with provable convergence of associated NN weights to their optimal values, thereby the learned knowledge can be ultimately stored and represented by the convergent constant RBF NN models. Based on this, an experience-based control scheme is further proposed, which is capable of recalling the associated learned knowledge in real-time to further improve control performance and reduce computational complexity with maintained provable stabilization. It is worth stressing that although this work is focused particularly on parabolic PDE systems, it is groundbreaking with important technical breakthroughs that would facilitate a more complete extension of the DL theory from traditional ordinary differential equation syste

关键词： Galerkin methods

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Development of automatic Cartesian Robot Cannabis Seeder using LabVIEW

Development of Automatic Cartesian Robot Cannabis Seeder usi...

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International ECTI Northern Section Conference on Electrical, electronics, Computer and Telecommunications engineering (ECTI-NCON)

作者： Rujipan Kosarat Keattipoom Sangwai Anan Wongjan Department of Software Engineering Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand Department of Electronic Engineering and Automatic Control Systems Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This article describes the invention of autonomous cannabis seeding equipment to reduce contamination and planting time. The automated cannabis seeder employs an NI myRIO control board to operate a y-axis stepper motor attached to a ball screw to move along the breadth of each row of 14 seed trays. Soil drilling and burial Drill all holes at the same depth. This promotes seed germination and lowers human-seed germ contamination. These 7 soil drill heads and 7 seeders use 3D printers to design and shape the workpiece. An 800-watt air pump smokes the cannabis seeds. Linear electric motors function in two rows in the z-axis. The buffer reverses the drowning process from row 14 to the first row, starting from the 3rd row and continuing through the final series of steps until 14 rows in the y-axis are complete. The hardware controls all program activities in LabVIEW. We tested the automated cannabis seeding machine 100 times on average, sowing cannabis seeds into 98 seed trays and dropping 93 seeds at 94.80% efficiency in 10.38 minutes. A 16 percent faster machine than human work is available.

关键词： Technological innovation Motor drives Shape Soil Pulse width modulation Three-dimensional printing Seeds (agriculture) Printers Robots Contamination

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A Hybrid Intelligence Model Forecasts the SOC of Electric Vehicle’s Battery 19th

A Hybrid Intelligence Model Forecasts the SOC of Electric ...

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19th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Rubiños, Manuel Arcano-Bea, Paula Timiraos, Míriam Michelena, Álvaro Vega, Rafael Vega Andújar, José Manuel Casteleiro-Roca, José-Luis CTC Department of Industrial Engineering CITIC University of A Coruña EPEF Calle Mendizábal s/n Campus de Esteiro A Coruña Ferrol15403 Spain Department of Electronic Engineering Computer Systems and Automatic University of Huelva Campus de El Carmen Huelva21071 Spain

ISBN: (纸本)9783031750090

Battery technology is advancing due to the demand of safe energy storage in systems such as Electric Vehicles (EVs) and portable electronics systems. Estimating battery conditions and increasing the range of electric vehicles requires specific models and optimize control strategies. Anticipate battery performance is complicated due to several variables, such as temperature, deterioration, and usage models. Knowing battery performance entails an advanced understanding of time series analysis, particularly forecasting. This study proposes the use of Artificial Neural Networks (ANN) to create a Lithium Ion Battery (LIB) prediction model. The experiments were carried out in a 59.2 VDC, 120 Ah LIB, recording the voltage and temperature while simulating the charge and discharge. A hybrid model is developed with internal local models using clustering. The model prognostic the State of Charge (SOC) evolution and reach a Mean Squared Errors with values between 10-3 and 10-4. This research shows that hybrid models are adecuated instrument for predict the battery SOC. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Artificial intelligent Batteries Electric vehicles SOC prediction

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Optimizing the LSTM Model for Electricity Price Forecasting Using the MSADBO Algorithm

Optimizing the LSTM Model for Electricity Price Forecasting ...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Ahmadvand, Fatemeh Imani, Mahmood Hosseini Andani, Hamid Taheri Andani, Mansour Taheri Politecnico di Torino Department of Control and Computer Engineering Torino Italy Torino Italy Isfahan University of Technology Department of Electronic Engineering Isfahan Iran School of Manufacturing Systems and Networks Arizona State University TempeAZ United States

ISBN: (纸本)9798331541125

Achieving accurate electricity price prediction is essential for market participants aiming to maximize their profits. In this respect, forecasting wholesale electricity market price plays a pivotal role. The advanced nonlinear modeling capabilities of deep learning networks have shown notable success in forecasting electricity prices. However, designing such networks, particularly selecting their optimal hyperparameters, still remains a big challenge. This paper presents a Modified Sine Algorithm Dung Beetle Optimization algorithm (MSADBO) as an improved Dung Beetle Optimization (DBO) algorithm to optimize the hyperparameters of the Long Short-Term Memory (LSTM) neural network to handle the electricity price forecasting in the Italian wholesale market. After optimizing the three most important hyperparameters of the LSTM using MSADBO, the efficiency of the model has shown a drastic improvement. Comparisons with conventional and machine learning-based approaches show that the LSTM-MSADBO model is highly precise in predictions with increased robustness and effectively captures volatility in the electricity market price. © 2025 IEEE.

关键词： Long short-term memory

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Bilateral Primary Frequency Support and AC Voltage Regulation of LCC-HVDC systems for Asynchronously Interconnected systems

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IEEE Transactions on Power systems 2025年第3期40卷 2600-2612页

作者： Li, Zhixuan Xue, Ying Chen, Yiping Chen, Nan Yang, Conghuan Huang, Jiyu South China University of Technology School of Electric Power Engineering Guangzhou510641 China China Southern Power Grid Power Dispatching and Control Center Guangzhou510663 China University of Birmingham Department of Electronic Electrical and Systems Engineering School of Engineering BirminghamB15 2TT United Kingdom Guangzhou Maritime University Guangzhou510725 China

Modern power systems require significant grid flexibility. As the AC transmission lines are passive and cannot be controlled, grid flexibility in the transmission system can only be provided by actively controlling High-Voltage Direct Current (HVDC) systems, particularly the dominant LCC-HVDC systems. Although grid-flexibility support using LCC-HVDC has been studied, existing methods fail to achieve bidirectional frequency support while maintaining AC voltage. Therefore, a coordinated control method is proposed for the LCC-HVDC system to achieve bilateral frequency support (BFS) and AC voltage regulation (AVR) for asynchronously interconnected systems. The level of frequency support and the coupled dynamics of sending-end (SE) and receiving-end (RE) system frequencies are quantified by the developed low-order frequency response model, different from frequency models in previous research for only one end of the system. With the developed model, the control parameters of the proposed method are analytically calculated. This ensures an appropriate level of primary frequency support without jeopardizing the frequency response of the system at the remote end. The effectiveness of the proposed method is demonstrated through real-time simulation. © 1969-2012 IEEE.

关键词： HVDC power transmission

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Locating Faults on Overhead Power Transmission Lines of 110 kV and Above Using Emergency Mode Parameters

Locating Faults on Overhead Power Transmission Lines of 110 ...

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International Youth Conference on Radio electronics, Electrical and Power engineering (REEPE)

作者： Dmitriy Sharygin Galina Filatova Andrey Yablokov Department of electric power systems automatic control Ivanovo State Power Engineering University (ISPU) Ivanovo Russia

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The article is devoted to the development of new fault location algorithms based on emergency mode parameters at instantaneous values on overhead power transmission lines of 110 kV and above. Increasing the accuracy of fault location algorithms is an important and urgent task. The methodological and simulation errors of fault location are directly related to the configuration of the power transmission line. The presence of parallel power transmission lines, mutual induction or branch substations affects the accuracy of fault location. In this work, the authors modernize their own previously developed fault location algorithms based on instantaneous values for complex power transmission line configurations. The developed fault location algorithms do not require additional corrections or means for processing primary signals and can be successfully applied when using data from digital in-strumental transformers. The studies of the algorithms were carried out on the simulation models of the overhead power lines in the Simulink/MATLAB software package. The remote fault location of the damage was carried out according to the parameters of the emergency mode. The assignment of parameters for the simulation modeling is carried out using the Monte Carlo method with subsequent statistical processing of the results and the construction of a justified inspection zone.

关键词： Instrument transformers Power transmission lines Accuracy Substations Voltage measurement Software packages Software algorithms Fault location Inspection Transmission line measurements

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A Unifying Complexity-Certification Framework for Branch-and-Bound Algorithms for Mixed-Integer Linear and Quadratic Programming

arXiv

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arXiv 2025年

作者： Shoja, Shamisa Arnström, Daniel Axehill, Daniel Division of Automatic Control Department of Electrical Engineering Linköping University Sweden Division of Systems and Control Department of Information Technology Uppsala University Sweden

In model predictive control (MPC) for hybrid systems, solving optimization problems efficiently and with guarantees on worst-case computational complexity is critical, particularly in real-time applications. These optimization problems often take the form of mixed-integer linear programs (MILPs) or mixed-integer quadratic programs (MIQPs) that depend on system parameters. A common approach for solving such problems is the branch-and-bound (B&B) method. This paper extends existing complexity certification methods by presenting a unified complexity-certification framework for B&B-based MILP and MIQP solvers, specifically for the family of multi-parametric MILP and MIQP problems that arise in, e.g., hybrid MPC applications. The framework provides guarantees on worst-case computational metrics, including the maximum number of iterations or relaxations B&B algorithms require to reach optimality. It systematically accounts for different branching and node selection strategies, as well as heuristics integrated into B&B, ensuring a comprehensive certification framework. By offering theoretical guarantees and practical insights for solver customization, the proposed framework enhances the reliability of B&B for real-time application. The usefulness of the proposed framework is demonstrated through numerical experiments on both random MILPs and MIQPs, as well as on MIQPs arising from a hybrid MPC problem. © 2025, CC BY.

关键词： Mixed-integer linear programming

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