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Real-Time Transaction Prediction Method Based on Generalized Tie-Line 1

International Top-Level Forum on Engineering Science and Technology Development Strategy and 5th PURPLE MOUNTAIN FORUM on smart grid protection and control, PMF2020

作者： Zhang, Yantao Jiang, Jingxiao Tu, Mengfu Xu, Fan Wang, Wen Nanjing Jiangsu211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing Jiangsu211106 China

ISBN: (数字)9789811597466

ISBN: (纸本)9789811597459

In order to cope with the rapid development of renewable energy in the Northwest Power grid, it is an urgent need to predict the renewable energy consumption capacity and transaction needs of the provinces, and promote the timely consumption of renewable energy within and between provinces. Therefore, this paper proposes a real-time transaction prediction method based on the generalized tie-line. Based on the definition of generalized tie lines, a multi-objective optimization model is established. The optimization objectives include positive and negative reserve of the provincial power grid and generalized positive and negative reserve of the main and sub-control areas. The method analyzes the power transmission and reception capacity and power transmission and reception needs of the main and sub-control areas in the next few hours, calculates the power purchase and sales capacity among the provinces, and automatically generates intra-provincial replacement and inter-provincial transaction plan based on the transaction rule library to enhance the intelligence level of renewable energy consumption in the Northwest Power grid. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Leakage flux-based method to identify the inrush current in transformers 12

Leakage flux-based method to identify the inrush current in ...

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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Zheng, Yu-Ping Zhang, Zhen-Ya Wu, Chong-Hao Pan, Shu-Yan Li, Zhou NARI Technology Co. Ltd State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

ISBN: (纸本)9781728170817

Inrush current occurrence in the power transformers is an unavoidable event that can happen due to energizing no-load transformer. Although various protection methods based on the terminal current and/or voltage have been proposed for transformer protection, the protection malfunction caused by the inrush current still occurs occasionally. In this paper, By comparing different closing angles of transformers with normal condition and differences in leakage flux near the yoke, a simple and accurate method is presented to identify transformer inrush current conditions. The change of the flux density on the leakage flux sensor can effectively identify the transformer inrush current. This identification method has been initially verified in the simulation in Maxwell. © 2020 IEEE.

关键词： Power transformers

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A Practical Method for Generating Day-Ahead Output Probabilistic Scenarios of Multiple Wind Farms Based on K-Shape Clustering 13

A Practical Method for Generating Day-Ahead Output Probabili...

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13th International Conference on Power and Energy systems, ICPES 2023

作者： Bo, Lin Xu, Taishan Tu, Mengfu Lu, Jinjun Nari Group Co. Ltd. State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (纸本)9798350345063

The volatility and uncertainty of wind power bring severe challenges to the power system, and the modeling of multi-wind farm output scenarios considering the uncertainty of wind power is of great significance in power system dispatching decision-making. Especially for area/ province with abundant wind power resources, where the reliability of the dispatching plan can be strongly affected by the volatility of large amount of wind power. In this paper, a practical method of generating probabilistic scenarios for day-ahead wind power output is proposed for provincial power grid with high proportion of wind power. Firstly, the K-Shape clustering algorithm is used to cluster the wind farm stations, and then the output scenario are generated by using the total wind power forecast value and forecast error probability distribution characteristics of each aggregated station. After arrangement and combination of the aggregated stations' scenes, the scenario minimization based on probability distance was conducted for clustering reduction to obtain the typical output scenes, and then the typical output scenes were assigned to each station according to the forecast value of the station to obtain the probability output scenes of each station. It is verified by actual power grid data that the scenarios generated by this method can combine with wind power predictions to well depict the random fluctuation of multi-wind farms output and has a good application prospect in the practice of day-ahead dispatching decision making. © 2023 IEEE.

关键词： Stochastic programming

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Marginal Unit Location Method Based on Dual Simplex Sensitivity Analysis 1

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7th Purple Mountain Forum on smart grid protection and control, PMF2022

作者： Zhang, Yantao Chang, Li Cao, Rongzhang Wang, Wen Zang, Zhendong Wu, Shuomin Jiangsu Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Jiangsu Nanjing211106 China

ISBN: (数字)9789819900633

ISBN: (纸本)9789819900626

With the continuous settlement and trial operation in the domestic power spot market, the price volatility analysis scenarios of the LMP widely used by power spot pilot provinces have gradually increased, and the real-time nature has gradually increased. Since LMP is affected by many factors, and different factors are coupled with each other, it is impossible to quickly and accurately analyze the reasons for node price fluctuations and pricing units. Therefore, combined with the domestic spot market clearing and pricing two-stage optimization strategy and the mature dual simplex theory, a marginal unit location method based on dual simplex sensitivity analysis is proposed. The method supports different scenarios such as unit independent pricing, unit, and constraint slack variable joint pricing, etc. The rationality of the positioning method is verified by the PJM 5 node and practical example. The results show that the method is universal and has been applied to several spot pilots. © state grid Electric Power Research Institute 2023.

关键词： Sensitivity analysis

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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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Capacitance Current Compensation Method for Cable-Overhead Hybrid Transmission Lines 5th

Capacitance Current Compensation Method for Cable-Overhead H...

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International Top-Level Forum on Engineering Science and Technology Development Strategy and 5th PURPLE MOUNTAIN FORUM on smart grid protection and control, PMF2020

作者： Yao, Gang Wu, Tonghua Zheng, Yuping Teng, Xianliang Hong, Feng Chen, Guozhou NARI Group Corporation Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

ISBN: (纸本)9789811597459

At present, the capacitance current compensation technology for transmission line differential protection is based on uniform parameters of entire lines, so it cannot be adapted to cable-overhead hybrid transmission lines. In this paper, a steady-state compensation method based on segment parameters, a time-domain compensation method based on whole line equivalent parameters and a time-domain compensation method based on segment parameters are proposed, which can adapt to different application scenarios, such as hybrid lines with shunt reactance at the ends and junctions. A PSCAD/EMTDC simulation shows that when a hybrid transmission line is short, the time-domain compensation method based on whole line equivalent parameters is simple to implement, and it can effectively compensate the capacitance current of hybrid transmission lines. The time-domain compensation method based on segment parameters can accurately compensate the capacitance current of hybrid transmission lines, taking into account the reliability and sensitivity of differential protection. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cables

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Prediction of Day-Ahead Electricity Price Based on N-BEATSx Model Optimized by SSA Considering Coupling Between Features 1

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7th Purple Mountain Forum on smart grid protection and control, PMF2022

作者： Xu, Feihong Teng, Xianliang Lu, Jixiang Zheng, Tao Jin, Yulong Nanjing211106 China NARI-TECH Nanjing Control System Ltd Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

ISBN: (数字)9789819900633

ISBN: (纸本)9789819900626

With the continuous advancement of Chinese electricity market reform, the continuous improvement of the market mechanism and the integration of a large number of new energy sources have brought great challenges to the market’s clear electricity price forecast. The new energy output, load data, and tie-line power schedule are fused to obtain an improved input feature variable, which can better reflect the electricity price trend. Then, the maximum information coefficient method (MIC) was used to analyze the correlation between each characteristic variable and electricity price, and an interpretable time series prediction model (N-BEATSx) based on neural network base expansion analysis of fusion characteristic variables was adopted. It is interpretable and can solve nonlinear forecasting problems of time series with the trend, seasonality, and significant random fluctuations. For the selection of hyperparameters in the N-BEATSx prediction model, the sparrow search algorithm (SSA) is used for optimization, the optimal grid structure hyperparameters are obtained with the minimum loss function of the validation set as the objective function. To verify the validity of the proposed model, the Shanxi Province market electricity price data is taken as an example to analyze and compare with other forecasting models, the results show that the proposed model can predict the electricity price of the day before clearing well. © state grid Electric Power Research Institute 2023.

关键词： Power markets

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An Integer Variable Reduction and Neighborhood Search Cutting Plane Method for Security Constrained Unit Commitment 4

An Integer Variable Reduction and Neighborhood Search Cuttin...

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4th International Conference on Power and Energy Technology, ICPET 2022

作者： Ding, Qia Ye, Jun Wang, Mengchang Zhang, Yantao Lu, Chunling Wang, Wen State Key Laboratory of Smart Grid Protection and Control Nanjing China Alibaba Group Alibaba Damo Academy Hangzhou China

ISBN: (数字)9781665480796

ISBN: (纸本)9781665480796

Security-constrained unit commitment (SCUC) is the foundation to ensure the safe and economic operation of power systems. A large number of integer variables and complex network security constraints are the main barriers that limit the computation efficiency of the SCUC problem. In this paper, the congestion information is used to identify the units that play a key role in alleviating transmission congestion, in the process of iterative solving of the SCUC. Then the commitment statuses of non-critical units are fixed, and the number of integer variables is reduced. Additionally, a neighborhood search cutting plane is designed and added to the model so as to reduce the branch-and-bound search space of the mixed integer programming problem. The simulation results of the 3375-bus case demonstrate that the proposed method can significantly improve the solving efficiency compared with the traditional method. © 2022 IEEE.

关键词： Complex networks

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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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Online Verification Method for Power grid Frequency Security Considering Multi-Time Scales Frequency Modulation Characteristics 16

Online Verification Method for Power Grid Frequency Security...

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16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024

作者： Sun, Zelun Zheng, Liang Li, Tong Luo, Feng Zhou, Haifeng Ruan, Jingjing Tian, Zhihao Laboratory of Smart Grid Protection and Control Nanjing China State Grid Ningxia Electric Power Company Ningxia China

ISBN: (纸本)9798350386127

With the large-scale integration of renewable energy such as wind power and photovoltaics, the power grid now exhibits characteristics of low inertia and reduced anti-interference ability. Consequently, it presents significant risks to the frequency security of the grid. The traditional online security verification of power grid frequency encompasses two distinct working conditions. Firstly, it involves the transient frequency security verification, which focuses on the primary frequency modulation during grid faults. Secondly, it also encompasses the medium and long-term security verification, specifically targeting the secondary frequency modulation under steady-state conditions of the power grid. This method cannot consider the multi-time scales factors of power grid frequency fluctuations. An online verification method for power grid frequency security considering multi-time scales frequency modulation characteristics is proposed. Based on the sliding filter algorithm, disturbance signals of different time scales are generated for simulation verification. Simulation methods are selected based on the fluctuation levels of disturbance signals at various time scales. By considering the priority of the primary and secondary frequency modulation time sequences of the power generating unit, an online security and stability verification method for grid frequency with consideration of multi-time scale frequency response is developed. The dynamic response process of the primary and the secondary frequency modulation of the system is simulated and verified based on the IEEE-39 system. © 2024 IEEE.

关键词： Frequency modulation

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