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检索条件"机构=DHunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology"

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A new method of short-term load forecasting based on the selection of compound variables

A new method of short-term load forecasting based on the sel...

引用

2021 IEEE International Conference on electrical Engineering and Mechatronics technology, ICEEMT 2021

作者： Yu, Xiao Wei, Zou Zhi, Ye Xiaoping, Liu Taoming, Zeng Huang, Rui Wenwei, Zeng Weijie, Zeng State Grid Hunan Electric Power Limited Company Changsha410004 China Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha410004 China

ISBN: (纸本)9781665441285

Accurate short-term load forecasting is an important guarantee for achieving lean operation and management of the power grid. However, there are difficulties in precise forecasting such as short-term load variability and selecting key factors of load forecasting. We establish a short-term load forecasting method based on variational modal decomposition and compound variable selection. The method is used to decompose the original power load data into multiple sub-sequences, and mine short-term load change characteristics while avoiding mode aliasing problems. Meanwhile, a complex variable selection algorithm is proposed to analyze and screen the key factors affecting load changes, effectively eliminating undesired data and further simplifying the complexity of the prediction model. Each sub-sequence is predicted and merged through the long and short-term memory neural network, achieving the final short-term load forecast. The verification results of the actual data of Changsha City selected for the entire year of 2019 show that the algorithm proposed here can accurately select the key influencing factors of load forecasting under complex external influence factors. With traditional forecasting models, the proposed model structure is simpler. The prediction accuracy is higher. © 2021 IEEE.

关键词： Forecasting

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Implementation of Asset Inventory Model Based on intelligent Algorithm

Implementation of Asset Inventory Model Based on Intelligent...

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Global Conference for Advancement in technology (GCAT)

作者： Liuqing Ye Canhui Zhang Dan Zhao Longmin Bu Huiting Xu State Grid Hunan Electric Power Company Limited Power Supply Service Center(Metrology Center) Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha China

Asset inventory is an important part of internal management in an organization, and it is of great significance for the smooth operation and normal development of the organization. The traditional manual inventory method has problems of low inventory efficiency and low accuracy. The asset inventory model based on intelligent algorithms can overcome the shortcomings of traditional methods and improve inventory efficiency and accuracy. This article introduces the implementation process of an asset inventory model based on deep learning algorithms. Firstly, the YOLOv4 algorithm is used for object detection to obtain the position and category information of the target object in the asset image. Then, the Faster R-CNN algorithm is used to locate the target, further improving accuracy. Finally, a neural network model trained on large-scale data is used to classify, recognize, and count assets. Using the actual data, this paper constructs the optimal portfolio model based on different risk measures and termination conditions: the maximization model of unit risk return, the VaR risk control model, and the risk return preference model. Genetic algorithm and Simulated annealing algorithm are used to optimize the model. Through experimental verification, the recognition rate of this model reaches over 90%, and the inventory efficiency and accuracy are greatly improved compared to traditional manual inventory methods. In summary, asset inventory models based on intelligent algorithms have unique advantages in inventory efficiency and accuracy, and have broad application prospects in the future.

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A Method and System for Evaluating Health Status of Low-voltage Power Supply Lines based on Clustering Algorithm 2021

A Method and System for Evaluating Health Status of Low-volt...

引用

The 4th International Conference on Information Technologies and electrical Engineering

作者： Minqi Yu Rui Huang Qin Liu Wenwei Zeng Maotao Yang Grid Hunan Electric Power Corporation Limited China and Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology China

ISBN: (纸本)9781450386494

In order to solve the problems of complex evaluation process and slow processing speed of existing low-voltage power supply line health evaluation methods, an evaluation method of low-voltage power supply lines health status based on Fuzzy C-Mean (FCM) clustering algorithm and Euclidean distance is proposed. First, the voltage and current values before and after the voltage and current changes are collected according to the equivalent circuit diagram of the low-voltage power supply lines, the loop impedance is obtained by the voltage and current values before and after the change. Then the loop impedance of a single user is clustered using the FCM clustering algorithm to find out the data that may have abnormal health conditions. Finally, based on the Euclidean distance, the above-mentioned data that may have abnormal health conditions are analyzed again to further determine whether the line is abnormal. The results of the case analysis show that this method has the advantages of accurate impedance data measurement, less workload, and ensuring normal power supply for users.

关键词： Line health status evaluation FCM clustering algorithm Low-voltage power supply line Euclidean distance

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Optimal Scheduling Method for Battery Energy Storage Based on Adaptive Time Granularity 7

Optimal Scheduling Method for Battery Energy Storage Based o...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Luo, Shuchen Wen, Ming Li, Wenying Liao, Jing Xiong, Dezhi Zhong, Yuan Power Economic and Technology Research Institute Key Laboratory of Hunan Province for Energy Internet Supply and Demand Operation State Grid Hunan Electric Changsha China Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology State Grid Hunan Electric Power Limited Company Power Supply Service Center Metrology Center Changsha China State Grid Hunan Electric Power Economic and Technology Research Institute Key Laboratory of Hunan Province for Energy Internet Supply and Demand Operation Changsha China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

With the integration of many intermittent and distributed new energy sources into the power grid, the safe and stable operation of the power system is facing huge challenges. HVAC (Heating, Ventilation and Air Conditioning, HVAC), electric vehicles (EV), and battery energy storage (BESS) can be a solution to this problem due to high flexibility and strong controllability. Aiming at the problem of power imbalance caused by large-scale wind power integration, this paper proposed an optimal scheduling method of HVAC and BESS based on adaptive time granularity. Time granularity is critical to the optimization of scheduling methods, which is decided by the load fluctuation in this paper. The simulation results showed that reducing the time granularity can smooth the fluctuation of the tie-line but would increase the scheduling cost and the amount of calculation. © 2022 IEEE.

关键词： Wind power

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Research and Expectation of a New Generation of Smart Energy Meter based on IR46 Standard 12

Research and Expectation of a New Generation of Smart Energy...

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12th International Conference of Information and Communication technology, ICTech 2023

作者： Xu, Wenlin Zhang, Peng Zeng, Weijie Liu, Chao Liu, Xi Wang, Xiangyu State Grid Hunan Electric Power Limited Company Changsha China State Grid Hunan Electric Power Limited Company Power Supply Service Center Metrology Center Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha China Power Supply Service Center Metrology Center State Grid Hunan Electric Power Limited Company Changsha China

ISBN: (纸本)9798350332919

With the acceleration of the construction of 'Smart Grid' and 'Advanced Metering Infrastructure (AMI)' worldwide, smart energy meter, as a key sensor and measurement point distributed on the network, should have functions such as communication, load control, online upgrade, parameter protection, legal measurement and non-metering partial isolation in addition to basic energy measurement. To this end, China newly revised JJF 1245-2019 standard fully adopts the 'Active Energy Meter' (IR46) formulated by the International Legal Metrology Organization, and stipulates the software and hardware requirements and type certification of the new generation of smart energy meters. This paper first discusses the requirements of a new generation of smart energy meters, compares the differences between IR46 and Chinese energy meter standard systems, introduces some key technologies of smart energy meters that support IR46 standards, and finally expounds the next research direction and application prospects of IR46 smart energy meters. © 2023 IEEE.

关键词： Advanced metering infrastructures

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Current Secondary Circuit Anomaly Detection Based on ROD Algorithm

Current Secondary Circuit Anomaly Detection Based on ROD Alg...

引用

IEEE International Conference on Power and Energy Systems (ICPES)

作者： Longmin Bu Rendong Zhang Hong Chen Shengwei Yang Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha China College of Artificial Intelligence Nanjing Agriculture Uinversity Nanjing China

During the operation of the power grid system, abnormal current often occurs due to equipment failure or improper operation by technicians. Timely detection of abnormal current sections plays a significant role in maintaining the safe operation of the power grid. In view of the low accuracy of current abnormal section detection methods, a robust Rotation based Outlier Detection algorithm that is parameter-free, requires no distribution assumptions is used to detect abnormal current segments. The preprocessed current data are used to train the model. The experimental results show that the method can detect abnormal current segments well.

关键词： Predictive models Prediction algorithms Power grids Data models Integrated circuit modeling Anomaly detection

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Research on Accurate Audit of Defaulting Power Consumption Based on K-Means Multidimensional Overrun Judgment

Research on Accurate Audit of Defaulting Power Consumption B...

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Yu Xiao Xingwang Yang Hanjun Deng Shuai Yang Zhi Ye Qinghong Guo Kejiang Xiao State Grid Hunan Power Supply Service Center (Metrology Center) Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha Hunan Province China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan Hubei Province China

With the rapid economic growth and the development of science and technology, the power supply is becoming increasingly tight. Some users use electricity in various ways in order to pay less electricity. The sudden increase of load not only increases the pressure of power enterprises to ensure power supply, but also disrupts the normal social order of power supply and consumption, and seriously damages the legitimate rights and interests of power supply enterprises. The traditional method of electricity default investigation has the disadvantages of difficult to check completely and accurately. To solve this problem, this paper based on $\mathbf{K}$ -Means clustering method to cluster analysis of daily frozen electricity data, combined with active power, load current and maximum demand data, to find out the abnormal points of electricity consumption, to form a multidimensional criterion, in order to realize the accurate inspection of the user's defaulted electricity consumption.

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Research on Multi-objective Coordination Strategies for Active Distribution Networks Based on Dynamic Energy Storage Management

Research on Multi-objective Coordination Strategies for Acti...

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Clean Energy and Electric Power Engineering (ICCEPE), International Conference on

作者： Huaping Yin Yeqin Ma Mouhai Liu Jiale Li State Grid Hunan Electric Power Limited Company Changsha China Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology (Power Supply Service Center (Metrology Center) State Grid Hunan Electric Power Limited Company Changsha China School of Electrical & Information Engineering Changsha University of Science & Technology Changsha China

ISBN: (数字)9798350390315

ISBN: (纸本)9798350390322

Aimed at the challenges posed by the increasing penetration of renewable energy sources (RES) in active distribution networks, particularly concerning local consumption and transmission barriers of harvested RES, this study investigates a coordination control methodology between distributed energy storage systems (ESS), volatile renewable power generation systems, and highly stable large-scale grid systems under secure operational conditions. Initially, the dynamic variations in charging and discharging depths during operation are considered, leading to a dynamic modeling of the state-of-charge (SOC) for ESS batteries. On the premise of ensuring the safety of distributed ESS, a multi-objective comprehensive optimization strategy is developed to enhance RES accommodation, augment regional grid RES export capability, and maximize economic benefits. Ultimately, the feasibility and rationality of the proposed strategy are validated through simulations, which demonstrate that the approach enables different storage units to adjust their charge-discharge depths, significantly improving the capacity for integrating renewable energy.

关键词： Economics Renewable energy sources Storage management Batteries Safety Power systems Active distribution networks State of charge Resource management Power generation

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New approach to select the fault line based on transient energy features of fault phase

New approach to select the fault line based on transient ene...

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2021 IEEE International Conference on Computer Science, Electronic Information Engineering and intelligent Control technology, CEI 2021

作者： Xiao, Yu Ye, Zhi Huang, Ru Liu, Mouhai Ma, Yeqing Wang, Jianzhong Zhao, Yantao Xu, Yong Wei, Xiongfei Teng, Zhaosheng Gao, Yunpeng State Grid Hunan Electric Power Limited Company Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha China Wasion Group Limited Changsha China College of electrical and information engineering Hunan University Changsha China

ISBN: (纸本)9780738146492

A new approach for fault line detection using Wavelet energy feature of fault-phase transient current is proposed. This novel method utilizes the phase selection function of insulation monitoring system and the differences of transient current between fault line and non-fault line. Firstly, the transient current signals of each phase fault are extracted to identify the faulty phase effectively. The pure fault component is obtained by noise elimination. Then, each phase wavelet energy feature can be achieved by the decomposition and reconstruction of wavelet packet. The fault line can be detected by comparing energy feature of each phase for the reason that the fault line's energy characteristics of fault phase are much greater than that of non-fault line under single phase grounding fault. This approach is clear in physical mechanism and unaffected by operating mode, circuit components, fault conditions and other factors. It can also effectively overcome the system noise, the interference of asymmetrical component. The line selection method has broad margin and high reliability, which is practical to applications. © 2021 IEEE.

关键词： Wavelet decomposition

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Research on the Source-Load Interactive Scheduling Strategy for Modern Industrial Parks 2

Research on the Source-Load Interactive Scheduling Strategy ...

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2019 2nd International Symposium on Power Electronics and Control Engineering, ISPECE 2019

作者： Haibo, Tan Kai, Li Mouhai, Liu Haiyuan, Wang Cong, Tan Zhiguo, Liu Changsha410004 China Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha410004 China

Aiming at the problems of diversified demand for electricity, high rate of load growth, limited distribution network corridor and single power supply mode in industrial parks, this paper explores a new scheduling strategy, studies a mechanism of source-load interactive scheduling for modern industrial parks, and puts forward three scheduling strategies, namely, optimal electricity price, friendly power grid and enhanced production. The strategy has been applied in a smart industrial park of Hunan Power Grid. The application results show that the method can effectively improve the power supply capacity of the modern industrial parks, reduce the total cost of electricity, and enhance the load rate of distribution transformers, and it also has high economic and practical value. © Published under licence by IOP Publishing Ltd.

关键词： Scheduling

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