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5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021

作者： Zhu, Yihua Chang, Dongxu Guo, Qi Guo, Hengdao Hu, Binjiang Wu, Mingkang Zhu, Yukun Yu, Duo State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation Control for New Energy Power System Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9781665434256

Based on the design characteristics of the stability control system, the control strategies of each station in the system are abstracted and integrated, and classified into standardized logic and customized logic. Based on the real-time digital simulation system platform, a three-layer architecture of the real-time simulation platform for the large-scale stability control system is designed. The standardized simulator based on FPGA/DSP and the customized simulator using device virtualization technology are designed in detail. The design scheme of the real-time accurate simulation platform for large-scale stability control system is proposed. From the perspective of hardware requirements, simulation accuracy, and platform adaptability, the differences between the simulation platform and the existing real-time digital simulation test platform are compared and analyzed. © 2021 IEEE

关键词： simulation platform

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Generation method of anti-misoperation locking logic rules for substations based on typical wiring

Generation method of anti-misoperation locking logic rules f...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Jingxiang Zhang Hui Zou Hewei Hou Junhui Li Rongrong Ji Kaiyuan Duan Cuiping Li Xingxu Zhu Extra-High Voltage Branch Company of State Grid Zhejiang Electric Power Co. Ltd Hangzhou China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

At present, substations usually use electrical blocking facilities to achieve the function of anti-fault blocking, but new stations and new reconstruction and expansion stations have the problem of low efficiency in the compilation and review of anti-fault blocking logic rules, and also need a lot of manual debugging and checking time. In this paper, based on the typical substation wiring and anti-false blocking logic rules, the typical substation wiring library and the corresponding blocking logic library are constructed; then, the graphic editing module and graphic analysis module are constructed by combining the substation modelling method with the topology and other technologies. Finally, the automatic generation of anti-error latching logic rules is realised, which solves the problems of low efficiency and lack of reliability in the writing and checking of the corresponding substation anti-misoperation locking logic rules.

关键词： Wiring Graphics Substations Reviews Debugging System integration Libraries Topology Logic Reliability

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Short-term power Prediction of Wind power Cluster Based on KOA-PLE

Short-term Power Prediction of Wind Power Cluster Based on K...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Nan Wu Mao Yang Chenglian Ma Yunpeng Jia Guozhong Fang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China Jilin Power Supply Company of State Grid Jilin Electric Power Co. Ltd Jilin China State Gird Northeast China Branch Jilin China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

With the gradual acceleration of the world's energy transformation, the construction of new energy is becoming more and more large-scale. At the same time, the proportion of new energy in the power grid is increasing, and the high volatility of wind power poses certain challenges to the stability and reliability of the power system. Therefore, accurate large-scale wind power prediction is very necessary. This paper presents a multi-task learning predicting method for wind power clusters. Firstly, the wind power cluster is divided into subgroups with similar output characteristics, and then the different subgroup power is used to predict the multi-task targets. Meanwhile, the Kepler optimization algorithm (KOA) is used to optimize the model parameters. When the method is applied to a wind power cluster in China, RMSE and MAE are reduced by 2.07% and 1.92% compared with the traditional multi-task learning method, which proves the effectiveness of the proposed method.

关键词： Learning systems Clustering algorithms System integration Wind power generation power system stability Multitasking Prediction algorithms Stability analysis Reliability Optimization

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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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Performance-Aware control of Modular Batteries For Fast Frequency Response

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IEEE Transactions on Sustainable Energy 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Massachusetts Institute of Technology Lab for Information and Decision Systems CambridgeMA02139 United States

Modular batteries can be aggregated to deliver frequency regulation services for power grids. Although utilizing the idle capacity of battery modules is financially attractive, it remains challenging to consider the heterogeneous module-level characteristics such as dynamic operational efficiencies and battery degradation. In addition, real-time decision making within seconds is required to enable fast frequency response. In order to address these issues, this paper proposes a performance-aware scheduling approach for battery modules to deliver fast frequency response (FFR) support. In particular, the conduction loss and switching loss of battery packs as well as converters are captured within a mix-integer quadratic constrained program (MIQCP). The cycle-based aging model identifies the aging cost of battery modules during frequent cycling by introducing the aging subgradient calculation and linearization. Case studies based on real-world battery data show that the proposed scheduling approach can effectively reduce power loss cost by nearly 28%-57% and battery aging cost by 4%-15% compared to conventional methods, which can also enhance the SoC balance. © 2010-2012 IEEE.

关键词： Battery management systems

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A Practical Fusion Localization Method for Autonomous Vehicles in Poor GPS Areas 5

A Practical Fusion Localization Method for Autonomous Vehicl...

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5th CAA International Conference on Vehicular control and Intelligence, CVCI 2021

作者： Deng, Jianqiang Chen, Jian Wang, Qi Zhang, Xinfang Zhejiang University State Key Laboratory of Fluid Power Mechatronic Systems College of Control Science and Engineering Hangzhou310027 China Zhejiang University State Key Laboratory of Fluid Power Mechatronic Systems School of Mechanical Engineering Hangzhou310027 China

ISBN: (纸本)9781665408462

Most of the existing intelligent vehicle navigation methods depend significantly on an accurate Global Positioning System (GPS). However, when the GPS signal drifts or loses, the navigation task will fail. To get rid of the influence of low precision positioning, we propose a novel fusion localization method for autonomous vehicles in low positioning accuracy areas. Specifically, key points with obvious features in the previous frame of the point cloud are extracted, converted to the next frame of the point cloud through the GPS data, and detect whether these features still exist to determine the GPS state at this time. Moreover, a detachable fusion positioning module based on LIDAR odometry is proposed and used for localization when the GPS signal is drifting or invalid. Furthermore, through real-world experiments, the proposed method was proven effective in the scene of GPS signal drift and failure. © 2021 IEEE.

关键词： Global positioning system

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Study of the Vibration Characteristics of 550 kV GIS Circuit Breaker Based on Rigid-Flexible Coupling Model*

Study of the Vibration Characteristics of 550 kV GIS Circuit...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yanpeng Ge Bo Liu Shaoshuai Su Yiheng Xu Qiang Sun Weikai Zhang Wensheng Gao Department of Electrical Engineering State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University Beijing China Shandong Taikai High Voltage Switchgear Co. Ltd Tai’an China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

High voltage circuit breakers (HVCBs) in the gas insulated switch gear (GIS) play an important role in the control and protection of power system. The mechanical faults account for the largest part of common faults in HVCBs. This paper establishes the rigid-flexible model of a 550 kV GIS HVCB, and experimentally studies the behavior characteristics of the HVCB under mechanical fault situation. Firstly, the fine 3D structure model of the 550 kV GIS HVCB is built and the arc-extinguishing principle of the HVCB is analyzed. Then, the rigid model and the rigid-flexible coupling model of the HVCB’s components and the whole system are established. The vibration signals of the two models are simulated and compared based on the finite element method. The component model mainly consists of the static arc contact and the dynamic arc contact. Furthermore, the mechanical fault is artificially set in the HVCB, and the vibration waveform are obtained. Finally, the simulation data is compared with the experimental results and the fault characteristics are analyzed. This research realizes the modeling, simulation and measurement of HVCB dynamic characteristics, which is of great significance to the diagnosis and prevention of HVCB mechanical faults.

关键词： Vibrations Couplings Solid modeling Three-dimensional displays Circuit breakers power system dynamics High-voltage techniques

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Operational Optimization of Photovoltaic-Storage System Considering Demand Response

Operational Optimization of Photovoltaic-Storage System Cons...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Xuefeng Gao Wenwen Qin He Wang Yiwen Yao Cuiping Li Hao Peng Xingxu Zhu Junhui Li State Grid Jilin Electric Power Company Limited Economic and Technical Research Institute Changchun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University China Songyuan Power Supply Company State Grid Jilin Electric Power Company Limited Songyuan China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

Aiming to address the stability challenges in power systems caused by the volatility and uncertainty of photovoltaic (PV) power generation, an optimization strategy for PV-storage systems incorporating demand response (DR) is proposed. Which is based on PV generation characteristics, Time-of-Use Pricing (TUP), and demand side flexibility. A multi-objective optimization model is established to balance the operational and environmental costs of PV-storage configuration. Building on dynamic adjustments at the demand side, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with dynamic inertia weighting is introduced to enhance global search capability for optimized energy storage (ES) configuration. In case study, two scenarios are designed to validate the effectiveness of the proposed model in reducing costs and improving PV utilization rates.

关键词： Photovoltaic systems Costs Uncertainty Heuristic algorithms Optimization models power system dynamics power system stability Demand response Optimization Load modeling

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Ultra-short-term power Prediction of Photovoltaic based on CNN-AM-BiLSTM

Ultra-short-term Power Prediction of Photovoltaic based on C...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Junhui Li Mingxuan Du Haozheng Yu Jie Ma Youwen Zhang Jiatao Gan Xingxu Zhu Cuiping Li Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China AnYang Power Supply Company State Grid HeNan Electric Power Company AnYang China Economic and Technical Research Institute State Grid HeNan Electric Power Company ZhengZhou China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

The power of photovoltaic power generation is affected by a variety of factors such as weather, radiation and temperature, exhibit a high degree of randomness and uncertainty. To address this problem, this paper proposes a ultra-short-term photovoltaic power prediction model based on Convolutional Neural Networks (CNN) and attention mechanism and bidirectional long short-term memory (Bi-LSTM). Firstly, Pearson's correlation coefficient was used to filter out the meteorological factors which have significant influence on the historical power. Subsequently, in order to capture the spatial features of the input data, a convolutional neural network is utilized for feature extraction and an attention mechanism is introduced to strengthen the model's ability to discriminate key features. Meanwhile, the Bi-LSTM network is utilized to capture the temporal dependencies in the time series data, and finally the PV power prediction value is obtained. Finally, the validation is based on data from actual PV power plants, and the results show that the proposed Convolutional Neural Networks and attention mechanism (CA) and Bi-LSTM Ultra-short-term PV power prediction model outperforms the single model in terms of prediction accuracy, reflecting the effectiveness and superiority of the hybrid model.

关键词： Photovoltaic systems Accuracy Attention mechanisms Time series analysis Weather forecasting Predictive models Feature extraction Data models Hybrid power systems Convolutional neural networks

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Risk Assessment with Generic Energy Storage under Exogenous and Endogenous Uncertainty

arXiv

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arXiv 2022年

作者： Qi, Ning Cheng, Lin Wan, Yuxiang Zhuang, Yingrui Liu, Zeyu State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China Tianjin University China

Current risk assessment ignores the stochastic nature of energy storage availability itself and thus lead to potential risk during operation. This paper proposes the redefinition of generic energy storage (GES) that is allowed to offer probabilistic reserve. A data-driven unified model with exogenous and endogenous uncertainty (EXU & EDU) description is presented for four typical types of GES. Moreover, risk indices are proposed to assess the impact of overlooking (EXU & EDU) of GES. Comparative results between EXU & EDU are illustrated in distribution system with day-ahead chance-constrained optimization (CCO) and more severe risks are observed for the latter, which indicate that system operator (SO) should adopt novel strategies for EDU uncertainty. © 2022, CC BY.

关键词： Energy storage

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