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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Yu, Jie Yang, Jiaqi Ding, Qia Tu, Mengfu Ji, Weixi Southeast University Electrical Engineering Nanjing China State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (纸本)9798350347159

The frequency regulation potential of temperature-controlled load aggregators means that, the total load reduction that all the aggregated temperature-controlled load users can participate in the frequency regulation. User demand response willingness refers to the willingness of users to adjust electricity consumption according to the price of electricity sales to provide demand response based on their own demand response elasticity. This paper establishes a user demand response willingness model including two parts of electricity cost change and temperature change, which is used to characterize the relationship between user frequency regulation potential and electricity price;then proposes a time series chained two-dimensional cloud generator algorithm for the willingness model to predict the temperature-controlled load operating state in the temperature-controlled load, and finally establish a two-layer model to optimize the frequency regulation potential of the temperature-controlled load aggregator, with the frequency regulation potential as the solution variable. The effectiveness of the algorithm and the model are verified through calculation examples, and sensitivity analysis is carried out. © 2022 IEEE.

关键词： Sensitivity analysis

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Research on intelligent evaluation model of transient stability based on K-means grouping 5

Research on intelligent evaluation model of transient stabil...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Ren, Xiancheng Zhang, Yin Wu, Feng Yuan, Huling Zhang, Jinlong Chang, Haijun Nari Technology Co. Ltd. State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

In a large number of actual power system operation scenarios, the transient instability scenarios are far smaller than the stable operation scenarios. In the case of imbalanced samples, the rapid transient stability assessment based on machine learning will lead to the learning algorithm preferring to the majority of classes with more samples, thus causing the problem of missing judgment for the transient instability scenarios. This paper proposes an under-sampling method for grouping majority class samples based on K-means. Under the constraint that the proportion of stable samples and unstable samples meets certain conditions, the majority of class stable samples are grouped with the center sample and the sample nearest to the center sample as initial values, and the K-means algorithm is adopted. By regrouping the samples of the majority class successively, multiple training sample subsets composed of unstable samples and multiple groups of stable samples are finally formed. Model training is performed for each training sample set, and the evaluation model of the new mode is judged by the comprehensive distance from the unstable center sample and the stable center sample of each sample subset, and then the transient stability judgment is carried out, so as to improve the accuracy of rapid evaluation under the unbalanced condition of training samples. The effectiveness of the proposed method is verified by an actual power grid example. © 2022 IEEE.

关键词： Learning algorithms

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Quantitative Intelligent Evaluation of Transient Power Angle Stability based on Cluster Grouping

Quantitative Intelligent Evaluation of Transient Power Angle...

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2022 Power System and Green Energy Conference, PSGEC 2022

作者： Ren, Xiancheng Xu, Taishan Zhang, Yin Bao, Yanhong Wu, Feng Zhang, Jinlong State Key Laboratory of Smart Grid Protection and Control Nari Technology Co. Ltd. Nanjing China

ISBN: (数字)9781665499934

ISBN: (纸本)9781665499934

Aiming at the problem that it is difficult to achieve the quantitative evaluation of transient power angle stability based on artificial intelligence, a quantitative intelligent evaluation method of transient power angle stability based on cluster grouping is proposed. Firstly, the key features of transient power angle stability are selected by the method of comprehensive physical mechanism and data mining. According to the difference requirement parameters of the key features of the train samples, the similar samples are minimized and clustered into groups. The center sample of each group is determined based on the comprehensive minimum of the stable mode difference index. Based on each group of center samples, a transient power angle stability margin estimation model is established and parameters are optimized by linear programming. Determine the effective group to which the new mode belongs by the effective mode distance of each group of samples. Use the model corresponding to each effective group to estimate the margin of the new mode, and take the minimum value of the estimated margin of all effective groups as the estimated value of the transient stability margin of the new mode to realize quantitative intelligent evaluation of transient power angle stability. The effectiveness of the proposed method is verified by an example of power grid. © 2022 IEEE.

关键词： Transients

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Energy Procurement and Retail Pricing for Electricity Retailers via Deep Reinforcement Learning with Long Short-term Memory

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1338-1351页

作者： Hongsheng Xu Jinyu Wen Qinran Hu Jiao Shu Jixiang Lu Zhihong Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China NARI Group Corporation Nanjing 211106China School of Electrical Engineering Southeast UniversityNanjing 210096China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106China

The joint optimization problem of energy procurement and retail pricing for an electricity retailer is converted into separately determining the optimal procurement strategy and optimal pricing strategy,under the“price-taker”*** aggregate energy consumption of end use customers(EUCs)is predicted to solve for the optimal procurement strategy vis a long short-term memory(LSTM)-based supervised learning *** optimal retail pricing problem is formulated as a Markov decision process(MDP),which can be solved by using deep reinforcement learning(DRL)***,the performance of existing DRL approaches may deteriorate due to their insufficient ability to extract discriminative features from the time-series vectors in the environmental *** propose a novel deep deterministic policy gradient(DDPG)network structure with a shared LSTM-based representation network that fully exploits the Actor’s and Critic’s *** designed shared representation network and the joint loss function can enhance the environment perception capability of the proposed approach and further improve the optimization performance,resulting in a more profitable pricing *** simulations demonstrate the effectiveness of the proposed approach.

关键词： Deep reinforcement learning electricity market energy procurement long short-term memory retail pricing

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Remote closed-loop test method of safety and stability control system based on step-by-step implementation 2

Remote closed-loop test method of safety and stability contr...

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2nd International Conference on Digital Society and Intelligent Systems, DSInS 2022

作者： Zhao, Wei Hou, Yuqiang Chen, Xiong Xue, Feng Chen, Wei Chen, Luofei Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China PONOVO Power Co. Ltd. Beijing100000 China

ISBN: (纸本)9781510663244

The safe operation of the safety stability control system is an important means to ensure the safe and stable operation of AC and DC power grids. Aiming at the shortage of existing test methods that cannot perform closed-loop testing of field safety stability control systems, a remote closed-loop test method for safety stability control systems based on step-by-step implementation is proposed. Using the simulation results of real-time digital simulation system (RTDS) as the signal source, a remote test platform architecture integrating laboratory and field safety and stability control devices is designed, key modules such as platform management system, test master and test terminal are developed, specific solutions are given for platform communication, and a remote closed-loop test procedure is formulated. Finally, a pilot application is carried out with an actual power grid security and stability control system as an example, and the effectiveness of the proposed method is verified. © 2023 SPIE.

关键词： Real time systems

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Comparison and improvement of key feature selection methods for intelligent assessment of transient power angle stability 5

Comparison and improvement of key feature selection methods ...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Zhang, Yin Xu, Taishan Ren, Xiancheng Bao, Yanhong Wu, Feng Zhang, Jinlong Nari Technology Co. Ltd. State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

key feature selection is of great significance for intelligent assessment of transient power angle stability of power system. This paper proposes a key feature selection method for improved Relief. Through analyzing and comparing the applicability of correlation coefficient, mutual information and Relief, three representative key feature selection methods, in the intelligent assessment of transient angle stability of power system, the applicability of Relief is better. The Relief index reflects the strength of the feature to classify transient power angle stability and instability. By eliminating redundancy and increasing the weight of unstable samples, the accuracy of index calculation and the ability to adapt to sample imbalance are improved. Based on improved Relief, feature is selected by iterative optimization, which can automatically screen out the optimal key feature set. The effectiveness of the method is verified by an example of power grid. © 2022 IEEE.

关键词： Transients

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Instantaneous Frequency Measurement and Tracking under Out of Step Oscillation 7

Instantaneous Frequency Measurement and Tracking under Out o...

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7th International Conference on Smart grid and Smart Cities, ICSGSC 2023

作者： Cai, Ke Su Zhang, Gan Feng Ji, Rong Rong Zheng, Sui Sheng Xia, Cheng Lin Lan, Tian Yu State Grid Electric Power Research Institute State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation NanJing China Ultra High Voltage Branch Company State Grid Zhejiang Powe Company HangZhou China Nari Group Corporation State Grid Eelectric Power Research Institute NanJing China

ISBN: (纸本)9798350305913

As an important operating parameter of the power system, the instantaneous frequency of the current can reflect the actual operating state of the current system, especially when the system is out of step. The characteristics of the current in the oscillation line are analyzed in this paper. An algorithm for measuring instantaneous frequency of current while power system swings is presented, based on the broad definition of angular frequency. According to the feature of the actual power system, a new method for measuring the instantaneous current frequency by real-time sampling is proposed. Finally, the algorithm is simulated on the model of the equivalent systems. When the system swings, the real-time frequency is gained by sampling the current in the line, combined with the frequency of the equivalent machine of both sides. It shows that the obtained current frequency is reasonable and effective, compared to the characteristics of the system. © 2023 IEEE.

关键词： angular frequency instantaneous frequency oscillation sampling

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A Coordinated MMC control Strategy of Integrated Photovoltaic/Battery System 7

A Coordinated MMC Control Strategy of Integrated Photovoltai...

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7th IEEE International Conference on Energy Internet, ICEI 2023

作者： Yang, Yuexi Zhou, Xiao Wang, Sichao Li, Chunpeng Huang, Junwei Xu, Wenzheng State Grid Smart Grid Research Institute Co. Ltd. State Key Laboratory of Advanced Power Transmission Technology Beijing China State Grid Fujian Electric Power Research Institute Fujian Key Laboratory of Protection and Operation Control for Smart Grid Fuzhou China National Research Center for Active Distribution Network Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350386684

The grid-connecting control and maximum power point tracking control of photovoltaic inverters have long been the research focus in the field of solar power generation. In this paper, a new coordinated modular multilevel converter (MMC) control strategy based on virtual synchronization and MPPT is proposed for grid-connected inverters in the PV/Battery system. The proposed strategy realizes frequency and voltage droop control with the synchro's inertia and damping characteristics, and improves the power angle stability as well as system voltage stability. Simulation results in MATLAB/Simulink verifies the feasibility and effectiveness of the proposed control strategy. © 2023 IEEE.

关键词： Solar energy

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Research on control Strategy of Transient Disturbance Based on the Three-level Hybrid Energy Storage Converter

Research on Control Strategy of Transient Disturbance Based ...

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2022 International Conference on New Energy, Energy Storage and Power Engineering, NESP 2022

作者： Chen, Jinyu Dai, Liyu Li, Zhicheng Deng, Chaoping State Grid Fujian Electric Power Research Institute Fuzhou China Fujian Key Laboratory of Protection and Operation Control for Smart Grid Fuzhou China

This paper proposes a control strategy of transient disturbance based on the three-level hybrid energy storage converter. The hybrid energy storage control strategy switches to the supercapacitor when the voltage sag occurs. Its characteristics of high power density can provide rapid and smooth voltage support for the distribution network so that the distribution network system will not be greatly affected by the impact. In the case of long-term voltage sag or power failure, it is important to switch to the energy storage battery and use its characteristics of high energy density to provide an emergency power supply to support the continuous operation of essential equipment. The control strategy proposed in this paper can realize the coordinated working between supercapacitor and energy storage battery and the fast and stable switching between two different working states of the energy storage system, which effectively solves voltage sag in the main power grid. Finally, a prototype is built, and the simulation and experimental results both verify the correctness and feasibility of the proposed control strategy. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Electric power supplies to apparatus

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DC operating circuit anomaly detection based on node voltage unsupervised time series 2

DC operating circuit anomaly detection based on node voltage...

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2nd International Conference on New Energy and Power Engineering, ICNEPE 2022

作者： Zhang, Shen Qi Yuan, Wei Yi, Ran Chen, Li State Grid NanTongPower Supply Company Jiangsu NanTong226000 China NARI Technology Nanjing Control Systems Co. Ltd Jiangsu Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Jiangsu Nanjing211106 China

With the increase in power system load, the number of switch cabinets increases rapidly, and the accidents caused by DC operating circuits become more and more obvious. Abnormal detection has become an important part of the DC operating circuit. Abnormal data, mainly voltage measurement, often contain important information. Finding and analyzing these abnormal data can give early warning for circuit failure or failure. However, abnormal data is often difficult to obtain and lacks marks, that is, the problem of sample imbalance and unsupervised problems, resulting in abnormal detection methods that can not meet the increasing accuracy and efficiency requirements. Generative adversarial network (GAN) is an unsupervised deep learning model, which has been successfully applied to unsupervised time series anomaly detection. However, GAN has technical difficulties in the anomaly detection process, and there is still room for optimization in accuracy. In this paper, the unsupervised time series anomaly detection method based on GAN is studied, and an anomaly detection method of a DC operating circuit combined with LSTM and GAN is designed. © Published under licence by IOP Publishing Ltd.

关键词： Generative adversarial networks

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