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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Walters, Michael Yonce, John Venayagamoorthy, Ganesh K. Clemson University Realtime Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson United States

ISBN: (纸本)9781665430654

Renewable energy generation sources (RESs) are gaining increased popularity due to global efforts to reduce carbon emissions and mitigate effects of climate change. Planning and managing increasing levels of RESs, specifically solar photovoltaic (PV) generation sources is becoming increasingly challenging. Estimations of solar PV power generations provide situational awareness in distribution system operations. A digital twin (DT) can replicate PV plant behaviors and characteristics in a virtual platform, providing realistic solar PV estimations. Furthermore, neural networks, a popular paradigm of artificial intelligence may be used to adequately learn and replicate the relationship between input and output variables for data-driven DTs (DD-DTs). In this paper, DD-DTs are developed for Clemson University's 1 MW solar PV plant located in South Carolina, USA to perform realistic solar PV power estimations. The DD-DTs are implemented utilizing multilayer perceptron (MLP) and Elman neural networks. Typical practical results for two DD-DT architectures are presented and validated. © 2023 IEEE.

关键词： Digital twin neural network power estimation solar photovoltaic

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Backup subscription scheme for differential protection using IEC61850-9-2 sampled values

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Energy Informatics 2024年第1期7卷 110页

作者： Katoulaei, Mohammad Khalili Rahmani, Aamir Høidalen, Hans Kristian Oleinikova, Irina Mork, Bruce Department of energy systems Norwegian University of Science and Technology Trondheim Norway Department of electrical power system Michigan Technical University Michigan United States Department of Electrical Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI49931 United States

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop simulation test bed. The main result is that BSS integration into differential protection ensures its dependability and security. Moreover, delay compensation and seamless switching feature increases the availability of differential protection. © The Author(s) 2024.

关键词： Hardware-in-the-loop simulation

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Functionalised B-Cu@F-Ag@Au trimetallic nanomaterials with long term stability for rapid and highly sensitive in situ SERS detection of furfural in transformer oil

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High Voltage 2023年第2期8卷 293-304页

作者： Yu Lei Changding Wang Weiping Kong Mingliang Wang Xinyuan Zhang Abdolmaleki Nima Caisheng Wang Weigen Chen Fu Wan School of Electrical Engineering Chongqing UniversityChongqingChina State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina Electrical and Computer Engineering Wayne State UniversityWayneNebraskaUSA

The surface-enhanced Raman scattering(SERS)substrates enable a highly sensitive detection of furfural in the transformer ***,detection substrates with long-term stability are still extremely *** this work,we anchored the thiol-containing coupling agents 2,5-dimercapto-1,3,4-thiadiazole(DMTD)and 1,4-benzenedithiol(BDT)on the surface of bubble copper(B-Cu)and flower-like silver nanoparticles(FAg),*** three-dimensional SERS detection substrates with long-term stability by using a combination of chemical reduction and self-assembly methods were *** substrate has a minimum detection limit of 10^(−9) M for rhodamine B in oil with an enhancement factor of up to 2.23×10^(7).Importantly,the three-crystal BCu@F-Ag_(1)@Au_(5) substrate was used for the detection of furfural in the transformer oil with a detection limit of 2 mg/L and a relative standard deviation value of 2.46%.After 60 days of a simulated operation,the detection signal of furfural in the transformer oil samples at 75℃ and still reached the initial value of 77.53%,indicating that the substrate has a good long-term *** triple frame structured SERS detection platform shows great potential in tracking furfural in the aging transformer oil mixing systems.

关键词： stability. stability SERS

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Coupon-based Demand Response for Consumers Facing Flat-rate Retail Pricing

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CSEE Journal of power and Energy systems 2024年第5期10卷 1887-1900页

作者： Hongxun Hui Yi Ding Kaining Luan Tao Chen Yonghua Song Saifur Rahman State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering University of MacaoMacao 999078China. College of Electrical Engineering Zhejiang UniversityHangzhou 310027China State Grid Jiangsu Electric Power Co. LTD.Nanjing 210000China School of Electrical Engineering Southeast UniversityNanjing 210096China Advanced Research Institute and Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State UniversityVA 22203USA

Even though smart meters have been widely used in power systems around the world,many consumers are still finding it hard to participate in demand response(DR)due to flat-rate retail pricing *** address this issue,this paper proposes a coupon-based demand response(CDR)scheme to achieve equivalent dynamic retail prices to inspire consumers’inherent ***,a security-constrained unit commitment optimization model is developed in the day-ahead market to obtain coupon rewards,which are then broadcast to consumers to motivate them to reschedule their power consumption *** evaluate the adjustment value of consumers’power consumption,a collective utility function is proposed to formulate the relationship between power quantity and coupon *** this basis,the security-constrained economic dispatch model is developed in the intra-day market to reschedule generating units’output power according to real-time load demands and fluctuating renewable *** the operation interval,a settlement method is developed to quantify consumers’electricity fees and coupon benefits on a monthly *** proposed CDR scheme avoids real-time iterative bidding process and effectively decreases the difficulty of massive,small consumers participating in *** proposed CDR is implemented in a realistic DR project in China to verify consumers’energy cost and renewables’curtailment can both be decreased.

关键词： Coupons demand response flat-rate retail pricing renewable energies small consumers

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Effect of Magnetic Couplings on Conducted EMI of GaN-Based PFC Converter 14

Effect of Magnetic Couplings on Conducted EMI of GaN-Based P...

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14th Annual IEEE Applied power Electronics Conference and Exposition, APEC 2025

作者： McGrew, Tyler Li, Qiang Virginia Tech Center for Power Electronic Systems The Bradley Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798331516116

Wide-bandgap power devices have enabled power supplies to increase in density while maintaining high efficiency. However, EMI issues remain one of the most challenging aspects when designing a power converter. These issues are often caused by parasitic near-field couplings which can degrade or bypass the attenuation of the EMI filter. This paper investigates how parasitic magnetic couplings impact the conducted noise of a high-frequency PFC converter using PCB-winding inductor. Analytical models are presented for both differential mode (DM) and common mode (CM) noise, including the effects of magnetic couplings between the PFC inductor and EMI filter. Then, three ferrite inductor core designs are evaluated to demonstrate how the core's geometry and permeability affect its leakage magnetic field. Choosing the optimal core design is shown to significantly reduce the magnetic field outside the PFC inductor, which reduces DM noise by more than 20 dB and reduces CM noise by 7 dB. © 2025 IEEE.

关键词： Magnetic levitation

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Broadband single-polarization single-mode low confinement loss hollow core anti-resonant fiber with semi-elliptical nested tube

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Optical and Quantum Electronics 2025年第4期57卷 1-12页

作者： Lin, Wen Fei, Yihong Wang, Ning Jia, Hongzhi Engineering Research Center of Optical Instruments and Systems Ministry of Education Shanghai Key Laboratory of Modern Optical Systems School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

In this paper, a hollow-core anti-resonant optical fibre containing a semi-elliptical nested tube is proposed, which has the characteristics of single-polarization, large bandwidth, single-mode and low confinement loss. By optimizing the structural design, the polarization extinction ratio (PER) of the fiber reaches 21,0183 at a wavelength of 1.55 μm, and the y-polarized fundamental mode loss is only 0.00086 dB/m. By changing the material and thickness of the semi-ellipsoidal nested tube, a large bandwidth of 280 nm was achieved in the wavelength range of 1.51-1.78 μm, with loss limited to less than 0.001 dB/m within the bandwidth range. The PER and higher-order mode extinction ratio of 4870, 1487, respectively. The loss remains below 0.01 dB/m when the bending radius exceeds 4.5 cm. Therefore, it is expected that this optical fiber can be used in optical devices such as fiber optic sensors, fiber optic lasers and fiber optic gyroscopes. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Single mode fibers

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Development of a High-Thrust Dual-Mover Transverse-Flux Linear Oscillatory Machine with Spoke PMs Embedded on Mover Yoke

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8617-8628页

作者： Li, Xiang Shi, Baoxu Huang, Wei Wu, Xinzhang Xu, Wei School of Electrical Engineering and the State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Guangxi University Nanning China State Key Laboratory of High Density Electromagnetic Power and Systems Institute of Electrical Engineering Chinese Academy of Sciences Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

In directly reciprocating drive systems, linear oscillatory machines (LOM) have the advantages of compact structure, high reliability, and high efficiency. However, although the Redlich-type LOM (RLOM) has been commercialized, it still has the demerits of low thrust density, large consumption of rare earth materials, and complex structure. Therefore, this paper proposes a novel moving-magnet transverse-flux linear oscillatory machine with spoke permanent magnets (PMs) inserted in dual mover yokes (HDTLOM), which has simpler laminated cores and higher thrust than the conventional LOMs. Benefiting from the spoke PMs flux concentration effect, the flux density is enhanced, which is beneficial for enhancing the thrust and reducing the PM consumption. Then, to optimize the electromagnetic performance, the main design parameters are classified by sensitivity analysis based on the finite element analysis (FEA). Consequently, the grid search and orthogonal experimental design (OED) are carried out for the optimal selection of the parameters, including the influence of both the axial and radial sizes on the performance. Afterward, some key indexes of the optimized HDTLOM are compared with the several conventional LOMs to verify its advantages. Finally, the machine is prototyped, of which performance improvement has been validated by the experimental tests. © 2015 IEEE.

关键词： Permanent magnets

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Design of a Remote Controlled Puppet Robot Imitating a Manual Driven Puppet Using Deep Learning Pose Detection 12

Design of a Remote Controlled Puppet Robot Imitating a Manua...

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12th RSI International Conference on Robotics and Mechatronics, ICRoM 2024

作者： Hamzeh, Hamed Shahroozi, Kiarash Nabipour, Ahmad Kazemi, Parham Malek-Zahedi, Mohammad Hallajian, Mehdi Moradia, Hadi School of Electrical and Computer Engineering College of Engineering University of Tehran Advanced Robotics and Intelligent Systems Laboratory Iran

ISBN: (纸本)9798331529734

Traditional puppet manipulation systems often require human operators to be physically present in tight and cramped locations. This leads to challenges in the positioning and effective operation of puppets, particularly in the presence of children in educational settings. In this paper, we present the design, development, and integration of a cost-effective robotic system for remotely manipulating puppets in real-time. Additionally, the system integrates a YOLOv8 Pose Detection model, trained on a custom dataset with an accuracy of 91.4%, enabling real-time gesture recognition and allowing the robot to be controlled by imitating the motions of a manually operated puppet. The system demonstrates the potential for many applications, including interactive entertainment, teleoperation, and education. © 2024 IEEE.

关键词： Gesture recognition

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Optimal Price-maker Trading Strategy of Wind power Producer Using Virtual Bidding

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Journal of Modern power systems and Clean Energy 2022年第3期10卷 766-778页

作者： Dongliang Xiao Mohamed Kareem AlAshery Wei Qiao IEEE Power and Energy Systems Laboratory Department of Electrical and Computer EngineeringUniversity of Nebraska-LincolnLincolnNE 68588-0511USA School of Electric Power South China University of TechnologyGuangzhou 510641China

This paper proposes a stochastic optimization model for generating the optimal price-maker trading strategy for a wind power producer using virtual bidding,which is a kind of financial tool available in most electricity markets of the United *** the proposed model,virtual bidding is used to improve the wind power producer’s market power in the dayahead(DA)market by trading at multiple buses,which are not limited to the locations of the wind *** optimal joint wind power and virtual trading strategy is generated by solving a bi-level nonlinear stochastic optimization *** upperlevel problem maximizes the total expected profit of the wind power and virtual bidding while using the conditional value at risk(CVa R)for risk *** lower-level problem represents the clearing process of the DA *** using the Karush-Kuhn-Tucker(KKT)conditions,duality theory,and big-M method,the bi-level nonlinear stochastic model is firstly transferred into an equivalent single-level stochastic mathematical program with the equilibrium constraints(MPEC)model and then a mixed-integer linear programming(MILP)model,which can be solved by existing commercial *** reduce the computational cost of solving the proposed stochastic optimization model for large systems,a method of reducing the number of buses considered for virtual bidding is proposed to simplify the stochastic MPEC model by reducing its decision variables and constraints related to virtual *** studies are performed to show the effectiveness of the proposed model and the method of reducing the number of buses considered for virtual *** impacts of the transmission limits,wind unit location,risk aversion parameters,wind power volatility,and wind and virtual capacities on the price-maker trading strategy are also studied through case studies.

关键词： Bi-level optimization electricity market risk management stochastic optimization virtual bidding wind power

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Distributed Deep Reinforcement Learning-based Approach for Fast Preventive Control Considering Transient Stability Constraints

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CSEE Journal of power and Energy systems 2023年第1期9卷 197-208页

作者： Hongtai Zeng Yanzhen Zhou Qinglai Guo Zhongmin Cai Hongbin Sun State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Automation Science and Technology Xi’an Jiaotong UniversityXi’an 710000China

Preventive transient stability control is an effective measure for the power system to withstand high-probability severe *** is mathematically an optimal power flow problem with transient stability *** to the constraints involved for differential algebraic equations of transient stability,it is difficult and time-consuming to solve this *** address these issues,this paper presents a novel deep reinforcement learning(DRL)framework for preventive transient stability control of power systems.A distributed deep deterministic policy gradient is utilized to train a DRL agent that can learn its control policy through massive interactions with a grid *** properly trained,the DRL agent can instantaneously provide effective strategies to adjust the system to a safe operating position with a near-optimal operational *** effectiveness of the proposed method is verified through numerical experiments conducted on a New England 39-bus system and NPCC 140-bus system.

关键词： Deep reinforcement learning preventive Control transient stability

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