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Characteristics of controlled Bridge Circuit and Its Application in Magnetic Field Induction Measurement

Tsinghua Science and Technology 2024年第4期29卷 1105-1117页

作者： Yanchu Li Qingqing Ding Mingchen Yan Jiyao Wang Jun Xu Xinzhou Dong Department of Electrical Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua UniversityBeijing 100084China School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 100096China

The article designs a new type of bridge circuit with a controlled source—when the resistance on the bridge arm of the controlled source bridge circuit meets the bridge balance condition, and the bridge branch contains only one Current-controlled Current Source (CCCS), a Voltage-controlled Current Source (VCCS), a Current-controlled Voltage Source (CCVS), or a Voltage-controlled Voltage Source (VCVS), the circuit is called a controlled bridge circuit, which has the characteristics of bridge balance. Due to the relationship between the controlled source and the bridge arm, the sensitivity of the components on the bridge is higher mathematically and logically. When applied to measurement, engineering, automatic control, and other fields, the controlled bridge circuit has higher control ac-curacy. Mathematical derivation and simulation results prove the correctness of the bridge balance conclusion and the special properties of this bridge when applied to the measurement field.

关键词： bridge bircuit bridge circuit applications bridge balanced condition controlled bridge circuit magnetic field induction measurement

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Planning of active power distribution network based on source-network-load collaborative optimization 16

Planning of active power distribution network based on sourc...

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16th IET International Conference on AC and DC power Transmission, ACDC 2020

作者： Jiang, Zhicheng Yu, Qingguang Li, Ang Xiong, Yufeng Long, Gaoxiang Liu, Yuming Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9781839533914

With the fast development of renewable energy generation, the randomness and volatility seriously threaten the stability of the power system. In order to improve the consumption rate of renewable energy and the economic benefit, the source-network-load collaborative optimization is put forward and widely used in the power system. And the active power distribution network which consists of the energy storage devices and flexible load is the best carrier to realize it. Based on the active power distribution network planning, this paper firstly designs an economic index covering construction cost and operation cost as the optimization objective. Then with the physical constraints consisting of the physical features of generation units, energy storage devices and flexible load, the source-network-load collaborative optimization model of active power distribution network is established. Finally, a case of city distribution network is presented to verify the effect of source-network-load collaborative optimization and the efficiency of the optimization model. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Optimization

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Short-term Photovoltaic Output Prediction Method Based on Similar Day Selection with Grey Relational Theory

Short-term Photovoltaic Output Prediction Method Based on Si...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Cui, Yang Zhang, Jiarui Zhong, Wuzhi Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Northeast Electric Power University Ji Lin China China Electric Power Research Institute Beijing China

ISBN: (纸本)9781728135205

With the rapid growth of Photovoltaic (PV) power capacity, how to improve the accuracy of PV output prediction becomes an intensive problem. This paper proposes a prediction model to reduce the error of prediction by combining gray correlation theory to select similar days with BP neural network. Firstly, the factors of weather between sample days selected as similar days and forecast days are calculated to find three similar days which have the highest relevance. After that, different weights are assigned to historical data of similar days according to the degree of relevance from large to small and back propagation (BP) neural network is combined to predict the output of PV. Finally, based on the actual measurement data of a photovoltaic power station in Northeast China, this paper validates the positive effects of this model on MATLAB simulation platform. Results show that selecting similar days by grey correlation and combining BP neural network can effectively improve the prediction accuracy of short-term PV output. © 2019 IEEE.

关键词： simulation platform

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Total supply capability and ideal total supply capability for distribution system: Definition, model and algorithm

Total supply capability and ideal total supply capability fo...

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作者： Xiao, Jun Zhai, Wei Gu, Wenzhuo Key Laboratory of Power System Simulation and Control of Ministry of Education Tianjin University 300072 China

ISBN: (纸本)9781457700668

This paper proposes the definition, model and algorithm of two quantitative indices named the Total Supply Capability (TSC) and Ideal Total Supply Capability (ITSC) for distribution planning. The TSC of a distribution system is comparable to Total Transfer Capability (TTC) in transmission systems, which is defined as the maximum load it can serve under the N-1 guideline for distribution systems, taking into account the capacities of the substation transformers, network link topology, link capacity, and other constraints. The ITSC of a distribution system is the calculated TSC which considers capacities of tie lines are large enough. Mathematical models for TSC and ITSC are set up and procedures to calculate TSC and ITSC are presented. Based on TSC and ITSC calculation, a concept named Potential Supply Capability(PSC) is proposed, which depicts the "potential" or "hidden" TSC of the distribution system. Finally, TSC and ITSC calculation have been performed in a test system with promising results. The case study has shown that TSC and ITSC algorithms are efficient approaches to analyze and evaluate the existing distribution system. © 2010 Chinese Soc for Elec Eng.

关键词： Electric utilities

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Real-time Optimal Energy Management of Combined Cooling, Heating and power systems Based on Knowledge conlusion 6

Real-time Optimal Energy Management of Combined Cooling, Hea...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： He, Chunjiang Wang, Yijian Xu, Yang Cui, Yang China Electric Power Research Institute State Key Laboratory of Power Grid Security and Energy Conservation Beijing China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9798350346671

Combined Cooling, Heating and power(CCHP) system is an important way to improve the efficiency of energy utilization and wind power consumption. In this case, increasing the operational flexibility of CCHP systems can help increase renewable energy consumption and reduce carbon emissions. So, it is necessary to provide real-time optimal energy management(OEM) for CCHP systems. In this paper. Firstly, a new training method is proposed for the LightGBM to improve the accuracy of real-time wind power prediction. In addition, to solve the nonlinear OEM of CCHP in real-time, a novel deep reinforcement learning algorithm-Soft Actor-Critic, is used in this paper. By combining the mechanism of CCHP with the reward function through knowledge fusion, the non-convex models can be translated into Markov Decision Processes(MDP), and then according to the Bellman optimal equation, the real-time optimized operation of the CCHP system is realized. Finally, the effectiveness of the proposed policy is verified by the actual operation data of a CCHP system in Northwest China. © 2023 IEEE.

关键词： Reinforcement learning

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Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

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Energy Engineering 2024年第9期121卷 2655-2680页

作者： Jiaxin Qiao Yuchen Hao Yingqi Liao Fang Liang Jing Bian Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy TechnologyMinistry of EducationJilin132011China State Grid Jiangsu Electric Power Co. Ltd.Power Dispatch Control CenterNanjing210017China State Grid Jiangsu Electric Power Co. Ltd.Nanjing Power Supply BranchPower Dispatch Control CenterNanjing210019China

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution *** accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response ***,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation *** this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation ***,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within ***,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of *** model can provide scientific guidance for the economic dispatch of the distribution station ***,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of th

关键词： Distributed photovoltaic distribution station area assessment of adjustment capacity line transmission capacity economic optimization

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Design of Planar Ultra-wideband Notch Antenna 19

Design of Planar Ultra-wideband Notch Antenna

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19th International Conference on Optical Communications and Networks, ICOCN 2021

作者： Zheng, Xuemei Xu, Xiuming Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China College of Information & Communication Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9781665424462

Ultra-wideband technology determines the development trend of the future society. As the core technology of ultra-wideband technology, ultra-wideband antennas are the most important structure in the radio system. When it is working, it will generate electromagnetic waves in free space and be converted into radio waves. There are many narrow-band frequency bands in the ultra-wideband frequency range (3.1GHz-10.6GHz). Use possible ways to make the antenna filter out other narrow-band interference in the working frequency band to realize the notch function. © 2021 IEEE.

关键词： Ultra-wideband (UWB)

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Distributed Coordinated Emergency Frequency control Strategy for Renewables-Rich power systems Based on Multi-Agent Reinforcement Learning

SSRN

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SSRN 2025年

作者： Sun, Zhenglong Han, Junpeng Chen, Weihan Zhang, Rui Liu, Yong Levron, Yoash Belikov, Juri Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion—Israel Institute of Technology Haifa3200003 Israel Department of Software Science Tallinn University of Technology Akadeemia Tee 15a Tallinn12618 Estonia

With the rapid growth of renewable energy in the power system and the implementation of large-capacity LCC-HVDC projects, the frequency support capability of the grid has been reduced. Simultaneously, the renewables-rich grid faces the risk of high-power shocks due to LCC-HVDC blocking. Existing centralized, single-measure approaches and the model-based emergency frequency control (EFC) methods are facing tremendous challenges. To fill this gap, this paper proposes a frequency emergency control method for renewables-rich grids that coordinates LCC-HVDC emergency power support and load shedding. The coordination of the two stabilization measures is modeled as a decentralized partially observable Markov decision process, and a multi-agent reinforcement learning (MADRL) approach is employed to optimize the power of measures for each stabilization control substation. An MADRL algorithm that integrates the system frequency response model is developed to overcome the problem of inaccurate evaluation of centralized action value in the MADRL algorithm used for EFC. This approach allows for the global optimization of the distributed coordination strategy through centralized training. The effectiveness and adaptability of the proposed method are demonstrated through simulations of the modified IEEE 39-bus system. © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Peaking Demand Analysis and Visualization simulation Platform Implementation of High Proportion of Wind power Infiltration Grid

Peaking Demand Analysis and Visualization Simulation Platfor...

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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Lv, Xiangyu Li, Dexin Li, Junhui Ge, Changxing Tian, Chunguang Wang, Jiarui Yan, Gangui Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd. Changchun China Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Jilin China

ISBN: (纸本)9781728143033

This paper proposes a analysis method of peak shaving demand for power grid, and analyzes the impact of wind power grid connection on power system peak shaving under different wind power permeability, and analysis the operational characteristics of energy storage assisted peak shaving to compare different energy storage systems. Finally, in order to facilitate the implementation and observation of the analysis results, a visual simulation platform was built. The results of the example show that the method described in this paper can accurately analyze the peaking shaving demand under different wind power permeability. At the same time, the total yield of lithium iron phosphate battery is the highest in the choice of energy storage type, which is 497 million yuan/year. All-vanadium redox flow batteries may benefit more than lithium iron phosphate batteries in the future due to battery characteristics. Finally, the visualization platform is true and effective and can fully express the method described in this paper. © 2020 IEEE.

关键词： Wind power

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A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

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Computers, Materials & Continua 2024年第9期80卷 4497-4512页

作者： Tianqing Yuan Na Li Hao Sun Sen Tan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Department of Electrical Engineering Northeast Electric Power UniversityJilin132012China College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China Center for Research on Microgrids Department of EnergyAalborg UniversityAalborg9220Denmark

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting ***,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data ***,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on ***,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available *** show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

关键词： Lithium-ion batteries state of charge state of health cyber-attacks genetic algorithm back propagation neural network

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