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SSRN 2024年

作者： Sun, Zhenglong Long, Hao Li, Zewei Gao, Bo Wei, Xiaoqiang Belikov, Juri Levron, Yoash Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy State Grid Jiashan County Power Supply Company Jiaxing China State Grid Heilongjiang Electric Power Company Limited Heilongjiang China The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion Israel Institute of Technology Haifa Israel Department of Software Science Tallinn University of Technology Tallinn Estonia Northeast Electric Power University China

The increasing interconnectivity of power systems and the integration of renewable energy sources into the grid have exacerbated the low-frequency oscillation problem, which directly impacts the stability of the power grid. The performance of wide-area damping control (WADC), which is an effective oscillation suppression technique , is susceptible to false data injection attacks (FDIA). This study proposes a non-intrusive data verification method using an adaptive variational autoencoder (AVAE) combined with a deep convolutional neural network (DCNN) to enhance WADC’s resistance to FDIA. The method integrates data dimensionality reduction of AVAE and reconstruction capabilities with DCNN’s feature extraction advantages. Itemploys adaptive thresholds to dynamically track grid data fluctuations, accurately distinguishing between normal and abnormal measurements and improving attack detection and performance discrimination. In addition, the study proposes an intelligent repair process based on latent representations for anomalous data in the repair module, using hierarchical clustering and Gaussian mixture models post-Bayesian inference to repair data. AVAE then reconstructs the repaired data, mitigating attack impacts. simulations on IEEE 39-Bus, 68-Bus, and 118-bus systems demonstrate that this method effectively detects network attacks and restores manipulated signals with minimal reconstruction errors, thus ensuring grid stability and reliability. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Coordinated Optimal Configuration Method of Wind power Load Shedding Rate and energy Storage Aiming at Active Frequency Support

Coordinated Optimal Configuration Method of Wind Power Load ...

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China International Electrical and energy Conference (CIEEC)

作者： Xiuyu Yang Jian Peng Yuxuan Liu Gang Miu Guochao Zhang Zhengyin Zhu Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeast Electric Power University Jilin China State Grid Xinjiang Power Supply Company State Grid Urumqi Power Supply Company Urumqi City China State Grid Jilin Power Supply Company State Grid Jilin Power Supply Company Jilin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

With the increase of renewable energy, the system frequency modulation ability is insufficient, and the relevant departments require that renewable energy should have the active support ability of power system frequency change. Long-term active load shedding to achieve frequency support will cause power generation loss and economic damage; if the maximum output of the wind turbine is taken as the active support task by the energy storage, the amount of energy storage required is large. Therefore, this paper proposes a coordinated optimal allocation method of wind power load shedding rate and energy storage capacity with the goal of frequency active support. From the economic point of view, the optimal allocation relationship between wind power load shedding rate and energy storage capacity allocation is analyzed to find the optimal setting of load shedding rate and energy storage capacity.

关键词： renewable energy sources Frequency modulation Costs Wind energy Load shedding Wind power generation Wind turbines

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Research on a New Integrated Device for Remote control of power Cable Testing and Cutting

Research on a New Integrated Device for Remote Control of Po...

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power system and New energy technology Innovation Forum (NPSIF), Boao New power system International Forum -

作者： Kangyangyong Cao Hongquan Xing Yilin Zhang Chuan Xue Feiyi Li Ziyang Gao State Grid Changchun Power Supply Company Changdian Group Cable Engineering Branch Changchun Jilin China Maintenance Department State Grid Changchun Power Supply Company Operation Changchun Jilin China Northeast Electric Power University engineering training and teaching center Jilin Jilin China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin Jilin China

ISBN: (数字)9798331504557

ISBN: (纸本)9798331504564

With the continuous improvement and development of urban power grid structures, it is inevitable that cable lines will need to be renovated and replaced. In the process of cable construction, the traditional cable cutting process involves independent operations, requiring a large amount of equipment and occupying a large area. Workers need to wear protective clothing when cutting, which is inflexible and inefficient. This approach is no longer adequate for the diverse and complex construction sites of today. To this end, a new type of integrated power cable cutting device is specially designed and developed, which combines testing and cutting, reducing the use of cable cutting tools. The newly developed circuit cutter is designed with features such as compact size, high structural strength, good cutting effect, strong adaptability, and remote control function. It can significantly improve the safety and convenience of cable cutting operations, which is of positive significance for improving construction quality and efficiency and ensuring the personal safety of operators.

关键词： Technological innovation power cables Protective clothing power system stability Reliability engineering power grids Safety power system reliability Remote control Testing

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DC fault ride-through for wind power integration via MMC-HVDC based on precise control of energy storage configured inside wind farm

DC fault ride-through for wind power integration via MMC-HVD...

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renewable power Generation and Future power systems Conference 2023 (RPG 2023 UK)

作者： Y. Sun Y. Guo F. Fan J. Fan G. Li Z. Wang X. Wu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin People's Republic of China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin People's Republic of China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow UK State Grid Smart Grid Research Institute Beijing People's Republic of China

The modular multilevel converter-based high voltage direct current (MMC-HVDC) overhead lines transmission scheme is the preferred option for wind power integration, though it is susceptible to DC faults. To ensure the connection of a wind farm (WF) to the grid during DC faults, this paper proposes a coordinated control strategy for DC fault ride-through (FRT) based on the energy storage system configured inside the WF for wind power integration through a bipolar MMC-HVDC. In the case of an instantaneous DC fault, the non-fault pole is regulated to operate at full power state to maximise wind power transmission. The exceedance of available wind power outputs over the transmission capacity of the non-fault pole is then accurately allocated to the internal energy storage units (ESUs) of wind generators (WGs) in order to ensure the power balance of the system and reduce the state of charge variance of ESUs as soon as possible. In order to reduce the energy capacities of ESUs required to store the excessive wind power in the event of a permanent DC fault, the method of step-by-step removing WGs is adopted to ensure the system power remaining balanced when the internal ESUs of the disconnected WGs are out of operation. The model is developed and carried out on the PSCAD/EMTDC simulation platform to verify the effectiveness of the proposed control strategies.

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Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

arXiv

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arXiv 2022年

作者： Li, Yang Wei, Xinhao Li, Yuanzheng Dong, Zhaoyang Shahidehpour, Mohammad The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States The ECE Department The King Abdulaziz University Saudi Arabia

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. Copyright © 2022, The Authors. All rights reserved.

关键词： Smart power grids

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Boosting Conversion Efficiency by Bandgap Engineering of Eco-Friendly Antimony Trisulfide Indoor Photovoltaics

SSRN

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SSRN 2024年

作者： Cao, Yu Li, Qiang Zhou, Jing Yu, Xiaoming Yu, Xuan Wang, Sanlong Li, Sen Pang, Jinbo Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Electrical Engineering School of Chemical Engineering Northeast Electric Power University Jilin132012 China School of Marine Engineering Equipment Zhejiang Ocean University Zhejiang Zhoushan316022 China Zhengzhou University of Light Industry China University of Jinan Shandong Jinan250022 China

With the exponential growth of the Internet of Things (IoT), indoor photovoltaics (IPVs) drawing heightened interest due to their adaptability to indoor environments. The Photovoltaic Conversion Efficiency (PCE) of IPV cells is critically dependent on their ability to match the indoor spectrum with the device's response characteristics. In this realm, Antimony Trisulfide (Sb2S3) emerges as a promising candidate for low-light applications. Our study focuses on the design and optimization of Sb2S3 thin-film IPV cells, aiming to refine both the device structure and its photoelectric performance for effective indoor light harvesting. In a strategic shift from conventional CdS materials, we utilized SnO2 as the electron transport layer (ETL) in Sb2S3 IPV cells. This substitution notably enhanced the short-wave response, elevating the spectral response from 45% to 80% at 400 nm. Additionally, we introduced a bandgap-tunable ZnOS buffer layer. This innovation proved instrumental in rectifying the band alignment mismatch between SnO2 and Sb2S3 layers, thereby optimizing interfacial electron transport properties. The resulting optimized Sb2S3 thin-film IPV cell demonstrated exceptional response characteristics across the full visible spectrum (400–750 nm) and showed notable photoelectric performance under both fluorescent lamps (FLs) and light-emitting diodes (LEDs). The device achieved a peak theoretical efficiency of 46.25% under cold white FL lighting, a testament to the optimal match between the device structure and this specific emission power spectrum. This research not only underscores the feasibility of employing antimony (Sb) -based photovoltaic technologies in indoor settings but also offers theoretical guidance for further advancements in this domain. © 2024, The Authors. All rights reserved.

关键词： Antimony compounds

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Iterative rational krylov algorithms for model reduction of a class of constrained structural dynamic system with engineering applications

arXiv

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arXiv 2021年

作者： Du, Xin Uddin, Mohammad Monir Fony, A. Mostakim Hossain, Md. Tanzim Shuzan, Md. Nazmul Islam School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Mathematics and Physics North south University Dhaka1229 Bangladesh Department of Mathematics Chittagong University Chittagong Bangladesh Department of Electrical and Computer Engineering North South University Dhaka1229 Bangladesh

This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody dynamics, mechatronics and many other branches of sciences and technologies. By deflecting the algebraic equations the second-order index-3 system can be altered into an equivalent standard second-order system. This can be done by projecting the system onto the null space of the constraint matrix. However, creating the projector is computationally expensive and it yields huge bottleneck during the implementation. This paper shows how to find a reduce order model without projecting the system onto the null space of the constraint matrix explicitly. To show the efficiency of the theoretical works we apply them to several data of second-order index-3 models and experimental resultants are discussed in the paper. © 2021, CC BY.

关键词： Differential equations

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Dual-layer economic dispatch method for electric fused magnesia loads participating in peak shaving guided by price compensation

Dual-layer economic dispatch method for electric fused magne...

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

作者： Junhui Li Tianzhen Fan Jing Xu Wei Zheng Chupeng Xiao Chaoyang Xu Cuiping Li Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin People's Republic of China State Grid Electric Power Research Institute Co. State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Co. Ltd. Hubei People's Republic of China State Grid Liaoning Electric Power Supply Co. State Grid Fushun Electric Power Supply Co. Ltd. Liaoning People's Republic of China

ISBN: (数字)9781837242924

To address the severe challenge of increasing fluctuations in supply and demand due to the expansion of new energy installations, this paper proposes a hierarchical optimization control strategy for electric fused magnesia loads participating in peak shav ing, guided by a price compensation mechanism. In the upper-layer system control, a price mechanism is designed to enhance the flexibility of electric fused magnesia loads in participating in peak shaving, considering the overall benefit of the system. In the lower-layer enterprise net profit optimization model, the product revenue, demand response income, operation and maintenance costs, and carbon emission costs of the electric fused magnesia enterprise are balanced to ensure the maximization of the enterprise’s net profit. Finally, numerical examples are used to verify the effectiveness of this method in improving the system's peak shaving capability.

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Multi-objective optimal dispatch method based on source-network-load-storage interaction system for DC distribution network

Multi-objective optimal dispatch method based on source-netw...

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International Conference on renewable power Generation

作者： Ran Quan Guoqing Li Guobin Jin Zhao Liu Qing Chen Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China State Grid Jiangsu Electric Power Co. Ltd. Nanjing China Jiangsu Electric Power Company Research Institute Nanjing China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The DC distribution network can integrate the photovoltaic power generation system with high efficiency, but the random fluctuation of the photovoltaic output power is strong and there is a problem of PV consumption, which has a certain degree of impact on the economic optimization operation of the system. Therefore, the source-network-load-storage optimization interaction concept is introduced in the DC distribution network. Based on the in-depth analysis of the interactive load characteristics, the interaction load and energy storage technology can be fully utilized to the system to consumpt the photovoltaic. Combined with the features of DC distribution network structure, comprehensively consider the impact of the interactive load and energy storage system collaborative optimization on the system operating cost and power flow distribution, so that both the power generation side and the power side can participate in the resource optimization configuration of the grid operation. A multi-objective optimal scheduling model for photovoltaic DC distribution networks with operational cost, network loss and voltage deviation is established. The simulation example shows that: Collaborative optimization using interactive load and energy storage system can greatly reduce system operating cost, network loss and voltage deviation, effectively improve the level of PV consumption, and realize safe and reliable operation of DC distribution network.

关键词： DC distribution network Distributed photovoltaic energy storage system Interactive load Optimal scheduling

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Research on load demand response behavior strategies in the steel industry guided by price signals

Research on load demand response behavior strategies in the ...

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

作者： Junhui Li Jiong Zhang Yan Li Peng Yu Meng Yu Hengyu Liu Xingxu Zhu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin People's Republic of China State Grid Electric Power Research Institute Co. Ltd State Grid Electric Power Research Institute Wuhan Efficiency Evaluation Co. Ltd Hubei People's Republic of China State Grid Liaoning Electric Power Co. Ltd State Grid Liaoning Electric Power Company Limited Power Dispatch and Control Center Liaoning People's Republic of China State Grid Liaoning Electric Power Co. Ltd State Grid Liaoning Electric Power Company Limited Electric Power Research Institute Liaoning People's Republic of China

ISBN: (数字)9781837242924

The steel industry load has the advantages of high power consumption, high automation level, strong controllability, and strong demand response potential. In order to improve its enthusiasm for participating in the power grid and promote the consumption of renewable energy, the electricity response behavior and demand potential of each production process of the industrial load are first evaluated. The strategy of using price signals to guide the steel industry load in typical areas to participate in the demand response of the power system is proposed. Models are established for the power grid dispatch center and the industrial load response behavior respectively. In the process, the different interests and demands of the two parties, the power grid dispat ch and the industrial load, are comprehensively considered. A two-layer dispatch model is established to truly reflect the interactive game process between power supply and demand; To match the model solution with interaction, a hierarchical iterative algorithm is used to accelerate the convergence speed while ensuring the interaction between price signals and purchasing power between layers. Combining a certain industrial load area for case analysis, the results show that the proposed model not only improves the system's ability to absorb renewable energy, but also takes into account the interests and responsiveness of the steel industry load.

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