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Power engineering Conference (SAUPEC), Southern African Universities

作者： Emmanuel Luwaca Senthil Krishnamurthy Department of Electrical Electronics and Computer Engineering Centre for Substation Automation and Energy Management Systems (CSAEMS) Center for Intelligent Systems and Emerging Technologies (CSIET) Cape Peninsula University of Technology Bellville South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

Communication plays a significant role in an electrical grid that includes Distributed Energy Resources (DERs). Modern control and automation systems used by these systems are predominantly distributed using domain standards such as IEC 61131-3. However, the IEC 61131-3 standard does not address communication. The IEC 61499 standard, in contrast, introduces the use of the Service Interface Function Block (SIFB) concept and high-level communication patterns to achieve hardware-independent access to communication services. This paper recommends the application of the IEC 61499 standard for DER control and automation and the application of SIFB to facilitate the ease of system integration in a DER plant. A low-cost gateway application using open-source IEC61499 tools is implemented, and its simulation results are presented.

关键词： Photovoltaic systems Power engineering automation Simulation System integration Logic gates Distributed power generation IEC Standards MATLAB Standards

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Distance Protection Application for 33kV Traction Network

Distance Protection Application for 33kV Traction Network

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Luthando Nkalitshana Senthil Krishnamurthy Haltor Mataifa Department of Electrical Electronics and Computer Engineering Centre for Substation Automation and Energy Management Systems (CSAEMS) Center for Intelligent Systems and Emerging Technologies (CSIET) Cape Peninsula University of Technology Bellville South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

The research investigates the laboratory-scale setup and functional testing of distance protection techniques for the Transnet traction system. The Transnet network, which powers South Africa's railway system, requires a strong protection mechanism to assure the safety and dependability of the electrical systems that power locomotives. Distance protection, essential in securing high-voltage transmission networks, is critical to detecting faults, isolating affected portions, and minimizing system interruptions. In this study, a simulation environment was created to simulate the features of the Transnet traction system, including traction substations, overhead power lines, and associated equipment. A lab-scale model was developed utilizing protection functional simulation to simulate real-time fault situations and evaluate the distance protection relay's response under different fault conditions. The performance and efficacy of the protection mechanism were assessed by varying key factors such as fault impedance, fault location, and fault types.

关键词： Rails Substations Simulation Reliability engineering Stability analysis Software Real-time systems Protection Load flow Testing

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IEC61850 GOOSE message application for a power transformer voltage control

IEC61850 GOOSE message application for a power transformer v...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Joniff Wellen Senthil Krishnamurthy Mukovhe Ratshitanga Department of Electrical Electronics and Computer Engineering Centre for Substation Automation and Energy Management Systems (CSAEMS) Centre for Intelligent Systems and Emerging Technologies (CSIET) Cape Peninsula University of Technology Bellville South Africa

ISBN: (数字)9798331535162

ISBN: (纸本)9798331535179

Voltage regulation of power transformers is critical to controlling and maintaining system voltage levels in the electrical transmission and distribution network system. It is vital to keep the transmission and distribution network's voltage levels within a specified range and to avoid voltage levels from fluctuating outside of the predetermined range of allowed tolerance levels. Two SEL-2414 IEDs were employed in this study to perform the voltage control function of the parallel power transformers using a master-follower control scheme. The automatic tap changers that execute this voltage regulating function incorporate the IEC61850 GOOSE message application as the communication protocol. The paper demonstrates the control function, a hardware-in-the-loop simulation in a closed-loop simulation using Real Time Digital Simulator (RTDS), and the two transformer tap changer IEDs SEL-2414 were utilized for lab-scale implementation and validating the simulation results.

关键词： Substations Protocols Hardware-in-the-loop simulation Reliability engineering Real-time systems Power transformers Tap changers Voltage control Protection Remote monitoring

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CONSTRUCTION PROGRESS MONITORING IN SMART CITIES USING DEEP ALEXNET

CONSTRUCTION PROGRESS MONITORING IN SMART CITIES USING DEEP ...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Rajavel, A. Karkuzhali, S. Sharma, Sarvdaman Singh, Sitesh Kumar Senthilkumar, P. Ida, S. Jhansi Electronics and Instrumentation Engineering Kamaraj College of Engineering and Technology Virudhnagar India Department of Electrical and Electronics Engineering R.M.D. Engineering College Chennai India Department of Civil Engineering University Institute of Engineering and Technology University of Jammu Jammu & Kashmir India Department of Civil Engineering Wollega University Nekemte Oromia Ethiopia KL School of Architecture Koneru Lakshmaiah Education Foundation Vaddeswaram Greenfield AP Guntur India Department of Computer Science and Business Systems R.M.K Engineering College India

ISBN: (纸本)9798350305708

Construction progress monitoring plays a crucial role in ensuring the timely and efficient completion of infrastructure projects within smart cities. This paper proposes a novel approach utilizing the Deep AlexNet architecture for construction progress assessment in smart cities. The Deep AlexNet model is trained on a diverse dataset of images captured from construction sites, enabling it to accurately analyze the visual cues indicative of construction advancement. By leveraging deep learning techniques, our system extracts and processes features from images, enabling automated and real-time progress evaluation. The proposed method contributes to enhancing construction management practices by providing stakeholders with a reliable tool to monitor and manage construction projects efficiently. Experimental results demonstrate the effectiveness and robustness of the Deep AlexNet-based approach in accurately assessing construction progress, thereby facilitating informed decision-making throughout the construction lifecycle. © 2023 IEEE.

关键词： Construction progress monitoring Deep AlexNet Deep learning Infrastructure projects Smart cities

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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Review of Planning and Optimization of the Renewable-Energy-Based Micro-Grid for Rural Electrification

Review of Planning and Optimization of the Renewable-Energy-...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Nteka Mojela Maletsie Senthil Krishnamurthy Department of Electrical Electronic and Computer Engineering Centre for Substation Automation and Energy Management Systems Cape Peninsula University of Technology Bellville Cape Town South Africa

The research work provides a comprehensive overview of the challenges and opportunities in the current energy landscape, particularly focusing on the role of microgrids in addressing the issues associated with the increasing energy demand, population growth, and technological advancements. The review addresses the rapid urbanization and population growth, coupled with technological advancements, have indeed led to an upsurge in energy demand globally. As suburban areas expand quickly, the demand for electricity in these regions rises, and traditional power grids may struggle to keep up with the increasing load. The mismatch between energy demand and generation poses a significant challenge. This can lead to power systems operating close to their limits, making them susceptible to disturbances and outages. The vulnerability of power system models to disturbances highlights the need for more resilient and adaptive energy solutions. Therefore optimal renewable-based microgrids are proposed as a promising alternative to reduce dependency on centralized power grids. Microgrids can enhance energy reliability, efficiency, and sustainability, particularly in areas where traditional grid infrastructure is lacking. Microgrids are identified as a solution for rural electrification, addressing both economic feasibility and long-term stability. The study aims to review the techno-economic aspects of microgrids, including the sizing and integration of Renewable Energy Sources (RES). The review addresses research gaps and implies a need for further exploration and development in microgrid-based energy management systems. Identifying and addressing these gaps will contribute to the effectiveness and efficiency of rural electrification. In summary, the study aims to provide a review summary of insights into the challenges and solutions associated with rural electrification through microgrids, emphasizing the importance of renewable energy sources and efficient energy management tech

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Application Perturb and Observe Maximum Power Point Tracking Technique for CubeSat Power systems

Application Perturb and Observe Maximum Power Point Tracking...

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Power engineering Conference (SAUPEC), Southern African Universities

作者： Khaya Dwaza Senthil Krishnamurthy Department of Electrical Electronic and Computer Engineering Centre for Substation Automation and Energy Management Systems Cape Peninsula University of Technology Bellville Cape Town South Africa

The Cube Satellite (CubeSat) power availability depends firstly on solar panel power generation and secondly on battery storage capacity. In a CubeSat mission, the solar panels must fit on the outside walls of a 10cm 3 volume. Hence, a maximum power point tracking (MPPT) technique is recommended for maximum usage of the available solar panel area to attain maximum solar power generation. A summary of (MPPT) techniques comparisons is discussed in this paper. An application of the perturb and observe (PO) MPPT technique is demonstrated using a DC-DC boost converter. When maximum point tracking is not applied to control the switching duty cycle of the pulse width modulator, the output current and voltage ripple erratically between minimum and maximum levels. However, when the MPPT technique is applied both the output current, and voltage settle at fixed levels.

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Optimizing Route Efficiency in Formula One (F1) Vehicles Using Reinforcement Learning Algorithms

Optimizing Route Efficiency in Formula One (F1) Vehicles Usi...

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AI in Cybersecurity (ICAIC), International Conference on

作者： Sanam Narejo Muhammad Taimoor Khan Muhammad Zakir Shaikh Lubna Luxmi Dhirani Bhawani Shankar Chowdhery Department of Computer Systems Mehran Univerity of Engineering and Technology Jamshoro Pakistan National Centre for Robotics Automation and Artificial Intelligence Mehran Univerity of Engineering and Technology Jamshoro Pakistan Mechanical Engineering and energy efficiency School of Industrial Engineering University of Malaga Malaga Spain Department of Electronic and Computer Engineering University of Limerick Limerick Ireland

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

This research explores the application of reinforcement learning (RL) to enhance route efficiency and performance of a Formula One (F1) car within a simulation environment. The simulation is implemented using Python, NEAT (NeuroEvolution of Augmenting Topologies), and PyGame to create a dynamic system where neural networks control the car’s navigation. RL enables the F1 car, acting as an agent, to learn optimal decisions through a fitness-based reward mechanism by interacting with its environment. Equipped with radar sensors to detect obstacles and measure distances, the virtual car adjusts its speed and steering to avoid collisions and optimize movement. Over successive generations, the RL algorithm refines the car’s driving ability, improving speed and directional control to maximize distance covered and minimize lap times. A fitness-based evaluation system tracks progress, providing metrics such as best and average fitness scores, which highlight the car’s evolving performance. Results demonstrate the effectiveness of RL in enhancing autonomous driving capabilities, enabling the car to navigate complex environments and improve decision-making across generations.

关键词： Navigation Tracking Neural networks Decision making Reinforcement learning Radar tracking Topology Sensors Automobiles Vehicle dynamics

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Robust Control of Metric Discrete Event systems Against Bounded Disturbances

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IFAC-PapersOnLine 2024年第1期58卷 108-113页

作者： Yiding Ji Xiang Yin Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Automation Shanghai Jiao Tong University Shanghai China

This work investigates robust supervisory control problems of discrete event systems modeled as finite state automata equipped with metric functions to measure the distance between states. The system may deviate from its nominal behaviors and fail to achieve the specification under disturbances whose effects are considered to be bounded. Accordingly, the supervisor should be designed to ensure that the controlled system degrades gracefully against such adversary. We formally formulate two problems: robustness bound verification and optimal robust supervisor synthesis. For the special case of verification under constant disturbances, a control Lyapunov function approach is introduced. Then we develop a two player game framework for the general verification and synthesis problems. Specifically, a dynamic programming method is proposed on the game structure, which uniformly tackles both problems.

关键词： Metric discrete event systems supervisory control robustness two player games

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

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