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4th IEEE International Conference on electrical Materials and power Equipment, ICEMPE 2023

作者： Meng, Pengfei Guo, Jingke Zhao, Long Lu, Wenhao Liu, Zheng Li, Shan Zhou, Kai Hu, Jun Sichuan University College of Electrical Engineering Chengdu China State Grid Corporatio of China State Grid Linyi Power Supply Company Linyi China Extra High Voltage Power Transmission Company of Csg High Voltage Technology Department Guangzhou China Northwest Institute of Nuclear Technology State Key Laboratory of Intense Pulsed Radiatio Simulation and Effect Xi'an China Tsinghua University State Key Laboratory of Control and Simulation of Power System and Generation Equipment Beijing China

ISBN: (纸本)9798350334678

As the core part of metal oxide arresters, ZnO varistor plays an important part in suppressing the overvoltage of power systems. With the development of UHV technology, the residual voltage and energy capacity of ZnO varistors have put forward higher requirements. The research is carried out from the perspective of material calculation, studied the correlation mechanism between micro-structure parameters and various macroscopic electrical characteristics of ZnO varistor based on Voronoi network. And the microstructure parameters such as grain size and size inhomogeneity were calculated and studied. The study simplified the optimization problem with multiple variates and objectives, into the one with two categories of variates and two categories of objectives. And then proposed specific strategies. The research provides important theoretical basis for improving the performance of ZnO varistors, and witch is of great significance for the design and manufacture of high-performance lightning arresters. © 2023 IEEE.

关键词： Microstructure

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Adaptive Time Period Aggregation for Day-ahead Unit Commitment

Adaptive Time Period Aggregation for Day-ahead Unit Commitme...

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2022 Tsinghua-IET electrical engineering Academic Forum, TDF 2022

作者： Yu, Zekuan Zhong, Haiwang Yan, Xinfei Department of Electrical Engineering Tsinghua University Beijing China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Beijing China

ISBN: (数字)9781839537998

ISBN: (纸本)9781839537998

The growing penetration of renewables calls for finer temporal resolutions of the day-ahead unit commitment (DA-UC) problem in order to accommodate the fluctuations and improve the performance of UC schedules, leading to the expansion of the DA-UC problem scale. However, due to its high computational burden, the viability of adopting larger UC models in practice becomes a challenge. In this paper, an adaptive time period aggregation strategy and a corresponding DA-UC model are proposed to reduce the model scale while preserving feasibility and accuracy. The aggregation strategy integrates the statistical characteristics of net demand with the operational characteristics of thermal units to effectively capture the consistency in on/off statuses. Case study based on the IEEE 118-bus system validates that, combined with a post-processing procedure, the proposed strategy and model can provide near-optimal UC schedules with approximately 5 times acceleration for various demand profiles, enhancing computational efficiency. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Computational efficiency

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Decision Support system for Adaptive Restoration control of Transmission system

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Journal of Modern power systems and Clean Energy 2021年第4期9卷 870-885页

作者： Ze Li Yusheng Xue Haohao Wang Lili Hao School of Electrical Engineering Southeast UniversityNanjingChina State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChina State Grid Electric Power Research Institute(NARI Group Corporation) NanjingChinaand they are also with State Key Laboratory of Smart Grid Protection and Operation ControlNanjingChina School of Electrical Engineering and Control Science Nanjing Tech UniversityNanjingChina

The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decision support framework for adaptive restoration control of transmission system is proposed, which can support the coordinated restoration of multiple partitions, coordinated restoration of units and loads, and coordination of multi-partition decision-making process and actual restoration process. The proposed framework is divided into two layers, global coordination layer and partition optimization layer. The upper layer partitions the transmission system according to the power outage scenario, constantly and dynamically adjusts the partitions during the restoration process, and optimizes the time-space decision-making of inter-partition connectivity. For each partition, the lower layer pre-selects restoration targets according to the estimated restoration income, optimizes the corresponding restoration paths, and evaluates the restoration plans according to the expected net income per unit of power consumption. During the restoration process, if the restoration operation such as energizing the outage branch fails, the current restoration plan will be adaptively switched to the sub-optimal one or re-optimized if necessary. The framework includes two operation modes, i.e., the on-line operation mode and training simulation mode, and provides an information interaction interface for collaborative restoration with related distribution systems. The effectiveness and adaptability of the proposed framework is demonstrated by simulations using the modified IEEE 118-bus system.

关键词： Transmission system restoration two-layer decision support framework restoration risk and income restoration uncertainty sand table deduction

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model

arXiv

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arXiv 2024年

作者： Dong, Xiaochong Dan, Jun Sun, Yingyun Liu, Yang Zhang, Xuemin Mei, Shengwei State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China College of Information Science & Electronic Engineering Zhejiang University Hangzhou310058 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Driven by global climate change and the ongoing energy transition, the coupling between power supply capabilities and meteorological factors has become increasingly significant. Over the long term, accurately quantifying the power generation of renewable energy under the influence of climate change is essential for the development of sustainable power systems. However, due to interdisciplinary differences in data requirements, climate data often lacks the necessary hourly resolution to capture the short-term variability and uncertainties of renewable energy resources. To address this limitation, a super-resolution recurrent diffusion model (SRDM) has been developed to enhance the temporal resolution of climate data and model the short-term uncertainty. The SRDM incorporates a pre-trained decoder and a denoising network, that generates long-term, high-resolution climate data through a recurrent coupling mechanism. The high-resolution climate data is then converted into power value using the mechanism model, enabling the simulation of wind and photovoltaic (PV) power generation on future long-term scales. Case studies were conducted in the Ejina region of Inner Mongolia, China, using fifth-generation reanalysis (ERA5) and coupled model intercomparison project (CMIP6) data under two climate pathways: SSP126 and SSP585. The results demonstrate that the SRDM outperforms existing generative models in generating super-resolution climate data. Furthermore, the research highlights the estimation biases introduced when low-resolution climate data is used for power conversion. Copyright © 2024, The Authors. All rights reserved.

关键词： Clean energy

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Erratum to:A mechanical reinforced and antifreezing polyacrylate hydrogel electrolyte for high-performance zinc-ion batteries

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Nano Research 2025年第4期18卷 658-658页

作者： Zili Zhang Ruolin Wang Hongfei Lu Di Zhang Yu Zhao Jing Xu Bin Sun Zhi-Min Dang Yang Jin School of Electrical and Information Engineering Zheng Zhou UniversityZhengzhou 450001China State Key Laboratory of Power System Operation and Control Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Erratum to:Nano Research,2025,18(1):***://***/10.26599/*** was an error in the second affiliation of the author“Zhi-Min Dang”in the published *** the online version of this paper is corrected.

关键词： electrolyte antifreezing zinc ion batteries mechanical reinforcement polyacrylate hydrogel

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Optimal scheduling of the electrolytic aluminium industrial park participating in flexible ramp products

Optimal scheduling of the electrolytic aluminium industrial ...

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4th Energy Conversion and Economics Annual Forum (ECE Forum 2024)

作者： Yaofei Sun Liang Han Yinxiao Li State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing People's Republic of China North China Branch State Grid Co. Ltd. Beijing People's Republic of China

ISBN: (数字)9781837242924

The integration of renewable energy sources (RES) into the power system has surged, posing significant challenges due to their inherent volatility and unpredictability. This paper examines the economic feasibility of electrolytic aluminium indust rial parks (EAIPs) participating in flexible ramping products (FRP) to enhance power system flexibility and improve economic benefits. We model the EAIP as a whole, detailing the flexible adjustment capabilities of electrolytic aluminium load (EAL) and establishing a two-stage operation model comprising Day-ahead (DA) and intraday planning. The DA model minimizes daily operational costs by determining electricity purchases and FRP participation based on forecast information, while the intraday model flexibly adjusts load power to accommodate real-time fluctuations in RES generation and FRP prices. The case study demonstrates that EAIPs can effectively reduce energy market purchase costs and increase FRP market revenue through power adjustment capabilities. Compared to operating without considering power regulation or FRP, the total expenditure in the case that includes both is reduced by 1.0%. The results highlight the potential of EAIPs to contribute to grid flexibility and economic efficiency in the context of RES penetration.

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The staged optimal scheduling method for a multi-source industrial park with wind, solar, thermal, and energy storage 3

The staged optimal scheduling method for a multi-source indu...

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3rd International Conference on Smart Energy and electrical engineering, SEEE 2024

作者： Hao, Ling Xu, Hui Tan, Zhenlong Zheng, Zhibao Xu, Fei Yang, Ruixuan Xu, Zhenyu Dai, Xuhui State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Co. Ltd. Beijing101199 China School of Economics and Management Tsinghua University Beijing100084 China State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing400044 China

The increase in the proportion of renewable energy generation capacity has placed significant pressure on thermal power operations. Constructing energy storage facilities within the metering output of thermal power plants, allowing them to participate in peak load regulation with generating units jointly, is one effective way to alleviate the operational pressure on thermal power. To achieve comprehensive scheduling of thermal power plants with energy storage, this paper first establishes an overall output model for the coupling operation of thermal power and energy storage. Secondly, a staged optimal scheduling method for a multi-source industrial park with wind, solar, thermal, and energy storage is proposed to solve the optimization scheduling problem for the industrial park involving thermal power plants with energy storage participation. Finally, the simulation results based on a specific regional power grid in Inner Mongolia validate the feasibility of the proposed method. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Thermoelectric power plants

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Optimal Configuration of Energy Storage Capacity in Wind-Storage Joint Frequency Regulation

Optimal Configuration of Energy Storage Capacity in Wind-Sto...

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power Science and Technology (ICPST), IEEE International Conference on

作者： Ling Hao Fei Xu Lei Chen Qun Chen Yong Min Yi Gu Yiming Chang Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China Department of Engineering Mechanics Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Tsinghua University Beijing China State Grid Liaoning Electric Power Co. Ltd. Liaoning China

We propose combining energy storage control with pitch control of wind turbines to give wind farms a primary frequency regulation capability similar to thermal power units. Using chance-constrained programming to handle the relationship between reliability and operating cost, and considering the full life-cycle cost of energy storage, we establish a chance-constrained programming model with the objective of minimizing the wind-storage joint frequency regulation operating cost. This achieves a trade-off between operating cost and reliability of the wind-storage frequency regulation system. We use the ant-lion algorithm to solve the model and obtain the optimal configuration of energy storage power and capacity for the wind farm, and compare the optimization results of the ant-lion algorithm with those of the particle swarm algorithm and the genetic algorithm. A case study is presented to verify the effectiveness of the proposed model and algorithm.

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Optimal design and techno-economic analysis of a desert off-grid photovoltaic-to-hydrogen system integrated with pipeline networks

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Energy Conversion and Management 2025年 336卷

作者： Xu, Jiaxin Lin, Jin Li, Jiarong Lin, Ruixiao Pan, Guangsheng Department of Electrical Engineering Tsinghua University Beijing China State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China Tsinghua-Sichuan Energy Internet Research Institute Chengdu China Harvard John A Paulson School of Engineering and Applied Sciences Harvard University Cambridge United States School of Electrical Engineering Southeast University Nanjing China

Addressing the challenge of harnessing remote solar resources for sustainable hydrogen production, this study presents a scalable off-grid photovoltaic-to-hydrogen (OgPVtH) system. We propose a bottom-up design methodology for the OgPVtH system, capturing the interconnections between land, water, and energy at micro and macro levels. At the micro level, we propose and consider the dynamic water-power-hydrogen characteristics of electrolyzers in a precise capacity allocation optimization model. At the macro level, we consider pipeline dynamic operating pressure constraints and establish a robust method for generating water-hydrogen pipeline network topologies. We conduct a real case study in the Hobq Desert. It reveals a levelized cost of hydrogen (LCOH) of 2.59 $/kg for the proposed OgPVtH system, indicating a 3.0 % lower cost compared to coal-based hydrogen production with carbon capture and storage (CCS) and 25 %-50 % lower cost compared to bioenergy to hydrogen, which demonstrates the system's economic competitiveness. The precise modeling of water-power-hydrogen characteristics and topologies can reduce LCOH by 0.35 $/kg and 0.01 $/kg, respectively. Sensitivity analysis highlights the trade-offs between investment in transmission and storage due to operational volatility, with an optimal hydrogen flow rate volatility of 80 % minimizing the total LCOH. © 2025 Elsevier Ltd

关键词： Hydro energy

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