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Study on Collaborative Planning and Allocation Method of Integrated Energy System Considering Dynamic Characteristics of Multiple Loads in Southwest Border Area 2

Study on Collaborative Planning and Allocation Method of Int...

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2nd International Conference on Smart grids and Energy Systems, SGES 2023

作者： Han, Shuai Lu, Jianbin Wu, Ning Xu, Xiufeng Qin, Yipeng Qiao, Biao Xue, Huiyu Electric Power Research Institute of Guangxi Power Grid Co. LTD. Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning China Chongzuo Pingxiang Power Supply Bureau of Guangxi Power Grid Co. LTD. Chongzuo China China Academy of Building Research Beijing China

ISBN: (纸本)9798350371659

The comprehensive promotion of the "Belt and Road"initiative and the "dual-carbon"strategy provides opportunities for the economic development of the Southwest border, but also puts forward high-quality development requirements. The rapid development of urbanization in the Southwest border region has caused a surge in the demand for building energy, as well as the dynamic characteristics of "season-geography". Therefore, it is of great significance to carry out collaborative planning and allocation methods of fixed resources and flexible resources to promote the efficient collaborative operation of the integrated energy system. This paper presents an integrated collaborative planning optimization method for fixed resource and flexible resource planning-operation of an integrated energy system taking into account the dynamic characteristics of multiple loads in the southwest border region. Aiming at the comprehensive optimization of economy, environmental protection, reliability and flexibility, and considering the characteristics of equipment and the dynamic characteristics of multiple loads of buildings, a planning optimization method combining fast non-dominated sorting genetic algorithm III with elite strategy and dynamic data envelopment analysis and Rank and ratio synthesis ranking method is adopted to realize the rational planning and allocation scheme of fixed resources and flexible resources in an integrated energy system. The results show that the proposed planning and operation integrated cooperative planning and allocation method can effectively improve the comprehensive performance of the integrated energy system, and has important practical significance for the cooperative planning and allocation of fixed and flexible resources in the southwest border area. © 2023 IEEE.

关键词： Data envelopment analysis

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Analysis of Harmonic Effects of High Voltage Circuit Breaker Asynchronous Motors under Different Frequency of SVPWM Vector control 4

Analysis of Harmonic Effects of High Voltage Circuit Breaker...

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4th International Conference on Information Science, Electrical, and Automation Engineering, ISEAE 2022

作者： Li, Rui Lu, Yufeng Su, Yi Zhang, Lei Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning530023 China

ISBN: (纸本)9781510655157

SVPWM vector control highly optimizes the harmonic, and has the characteristics of fast dynamic response and small torque ripple. For this reason, under the SVPWM vector control strategy, only the carrier frequency is changed to simulate and analyze the influence of different carrier frequencies on harmonics. This paper first analyzes the sampling principle of SVPWM, and establishes the model of carrier frequency and harmonics relationship. Then, this paper simulates the asynchronous motor system under SVPWM vector control, analyzes the stator current, rotor speed and torque waveform, and can get the characteristics of low harmonics, fast dynamic response and small torque ***, the A-phase stator current is taken as an *** the carrier frequency is changed to take 3KHz, 4KHz and 5KHz for FFT analysis. Comparing the THD of the three,it can be concluded that the larger the carrier frequency, the smaller the THD, the smaller the harmonic loss. © 2022 SPIE.

关键词： Induction motors

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Analysis and Treatment of Abnormal Defects in Transformer Oil Chromatography 4

Analysis and Treatment of Abnormal Defects in Transformer Oi...

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2022 4th International Conference on Energy Systems and Electrical power, ICESEP 2022

作者： Li, Rui Zhang, Lei Chen, LiangYuan Li, DaJian Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning530023 China

This article analyzes the cause of an abnormal defect in the oil chromatogram of a transformer, and puts forward control measures and suggestions. It is analyzed that the cause of the abnormal oil chromatogram of phase A and B of the main transformer is the poor contact o f the dynamic and static contacts of the unloaded tap changer, high temperature and overheatin g, and the development of contact ablation, resulting in abnormal oil chromatogram. The cause of the ablation of the dynamic and static contacts of the no-load tap-changer may be due to the installation and transportation (or electrodynamic shock or U-switch design and other factors), the contacts are not in close contact, the larger contact resistan ce causes the contacts to overheat, and high temperature conditions Sulfur corrosion occurs on the surface of the lower contact, and the corrosion product gradually deposits on the surface of the contact, which further aggravates the poor contact. Although passivation agent is added in t he later period, the protection effect of the passivation agent at high temperature is limited, and it can no longer protect the contact. Under the action of current, the dynamic and static contacts that cause poor contact are gradually ablated. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Passivation

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An Auxiliary Decision-Making Model through Comprehensive Utilization of Multi-type Active power Adjustment Resources

An Auxiliary Decision-Making Model through Comprehensive Uti...

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International Conference on power and Energy Technology (ICPET)

作者： Zhengping Chen Fangdong Wang Xichen Tian Yan Lv Wenjian Wang Zhi Cai State Grid Fujian Electric Power Dispatching and Control Center State Grid Fujian Electric Power Company Fuzhou China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (数字)9798350375855

ISBN: (纸本)9798350375862

As the construction of the new power system progresses, the marked increase in the penetration rate of renewable energy, the intensified coupling of multi-energy systems, the closer interconnection among regional power grids, and the accelerated advancement of electricity market reforms have significantly heightened the complexity and uncertainty of the system. These developments pose substantial challenges to the existing dispatching technologies. In this paper, an auxiliary decision-making model through comprehensive utilization of multi-type active power adjustment resources is proposed. Firstly, the paper presents the framework of the auxiliary decision-making model. Then, the paper proceeds meticulously to establish the auxiliary decision-making model, including variables, the objective and constrains. Finally the validity of the model is verified using actual grid data from a specific region.

关键词： Solid modeling Uncertainty power supplies Decision making dispatching Regulation power grids Security Synchronization Load modeling

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Parameter Extraction of Photovoltaic Models Using a Dynamic Self-Adaptive and Mutual- Comparison Teaching-Learning-Based Optimization

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IEEE ACCESS 2021年 9卷 52425-52441页

作者： Li, Lei Xiong, Guojiang Yuan, Xufeng Zhang, Jing Chen, Jinlong Guizhou Univ Coll Elect Engn Guizhou Key Lab Intelligent Technol Power Syst Guiyang 550025 Peoples R China Guizhou Elect Power Grid Dispatching & Control Ct Guiyang 550002 Peoples R China

Parameter extraction of solar cell models plays an important role in the simulation, evaluation, control, and optimization of the photovoltaic (PV) system. Although many meta-heuristic algorithms have been proposed to solve the parameter extraction, it is necessary to further improve the accuracy and reliability of these algorithms. In this paper, an optimized teaching-learning-based optimization (TLBO) is proposed, namely dynamic self-adaptive and mutual-comparison teaching-learning-based optimization (DMTLBO). DMTLBO enhances the basic TLBO by improving its teacher phase and learner phase: (i) In the teacher phase, two differentiated and personalized teaching strategies are proposed according to learners' learning status. In these two strategies, an adaptive state transition weight factor omega and a dynamic gap weight factor beta are introduced to reflect the dynamic transformation of the learners' learning state in the actual teaching situation. (ii) In the learner phase, a new learning strategy is proposed. The learner can communicate and learn with three different learners who are randomly selected and ranked. To verify the performance of the DMTLBO algorithm, it is used to extract the parameters of different PV models, such as the single diode model, the double diode model, and three PV modules. Among these PV models, the root mean square error values between the measured data and the calculated data of DMTLBO are 9.8602E-04 +/- 2.07E-17, 9.8248E-04 +/- 1.53E-06, 2.4251E-03 +/- 2.15E-17, 1.7298E-03 +/- 5.74E-14, and 1.6601E-02 +/- 4.55E-10, respectively. Compared with other optimization algorithms, the experimental results show that DMTLBO can provide better or highly competitive convergence speed and extraction accuracy. Besides, the influence of the improved teacher phase and learner phase on DMTLBO and the changing process of both weight factors omega and beta are investigated.

关键词： Optimization Integrated circuit modeling Heuristic algorithms Semiconductor diodes Parameter extraction Equivalent circuits Education Photovoltaic parameter extraction teaching-learning-based optimization

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Accurate comparison method of load data of power outage events of users 2

Accurate comparison method of load data of power outage even...

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2nd International Conference on Electrical Engineering and control Science, IC2ECS 2022

作者： Yi, Chenying Zhou, Yangjun Electric Power Research Institute of Guangxi Power Grid Co. Ltd Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning530023 China

ISBN: (纸本)9798350399165

In this paper, aiming at the problems of low accuracy and difficulty in comparison of existing customer power outage load data, an accurate comparison method of customer power outage load data is proposed, which includes multiple linear regression model and verification, residual diagram auxiliary analysis, F and R test and accurate method comparison. In this paper, multiple linear regression is adopted, considering the influence of daily maximum temperature, daily minimum temperature, daily average temperature, precipitation, humidity and other factors on the load data model of power outages. Every time an independent variable is introduced, the variables already in the equation will be F-Tested, and the variables that meet the elimination criteria will be eliminated one by one. In addition, residual diagram auxiliary analysis, F and R tests will ensure the accuracy of the processed load data of power outages and eliminate adverse effects. Error RES and R2 goodness-of-fit test are used for comparison. Compared with traditional methods, many methods are used to ensure the accuracy of data in the process of data processing, which greatly improves the reliability of data comparison. © 2022 IEEE.

关键词： Multiple linear regression

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Intra-Day Rolling Optimal Strategy Considering Whole Dispatch Process and Multi-Type Adjustable Measures

Intra-Day Rolling Optimal Strategy Considering Whole Dispatc...

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IEEE International Conference on power and Energy Applications (ICPEA)

作者： Wenzhong Li Duanhong Zhang Xichen Tian Yan Lv Zhengqi Xu Jingfeng Liang State Grid Fujian Electric Power Dispatching and Control Center State Grid Fujian Electric Power Company Fuzhou China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

The current electric power system practices hierarchical and zonal administration to facilitate more effective monitoring of grid safety and event management. With an escalating integration of new energy sources on the generation side, the intrinsically variable nature of these resources introduces substantial uncertainties into grid operations. Meanwhile, on the demand side, load profiles are diversifying further, significantly influenced by weather conditions, market price signals, or incentive schemes, thereby adding another layer of unpredictability. Against this context, this paper proposes an intra-day rolling optimal strategy considering whole dispatch process and multi-type adjustable measures. By synthesizing regulating resources from both the source and load sides, it undertakes a series of intra-day rolling optimization decisions across the entire dispatch workflow. This strategy aims to harmonize and optimize the allocation of various resources, thereby ensuring the secure and stable functioning of the electrical grid amidst the complexities introduced by the integration of intermittent renewables and the dynamics of diversified loads.

关键词： Renewable energy sources power measurement Uncertainty power supplies Process control Robustness Safety power system reliability Resource management Optimization

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Adaptive Identification of power System Operational States Based on Spatio-Temporal Dynamic Graph Neural Networks

Adaptive Identification of Power System Operational States B...

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Electronic Technology, Communication and Information (ICETCI), IEEE International Conference on

作者： Qingqing Zhang Qinfeng Ma Mingshun Liu Jie Zhang Yihua Zhu Zhuohang Liang Su An Qingxin Pu Jiang Dai Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

The state identification of the operational status of power systems plays a crucial role in ensuring the safety, efficiency, and reliable operation of power systems, forming the foundation for the management and control of power system operations. In the practical operation of power systems, the duration of fault states is short, while the system remains in a safe and stable state for a significantly longer period, leading to an imbalance in the training samples available. This imbalance can cause traditional machine learning classification algorithms to favor the majority categories of power system operational states, resulting in inaccurate evaluation metrics and reduced model generalization capability. To address this issue, this paper introduces a spatiotemporal dynamic graph neural network model for the identification of power system operational states. By incorporating class cost coefficients, focal loss, and cross-entropy in a joint loss function, the model adaptively focuses on the less represented operational state categories during training, improving classification accuracy on imbalanced and challenging samples. Moreover, the integration of temporal information and spatial topology information within the graph neural network enhances the model’s robustness and generalization ability in state identification. Experimental results on the standard IEEE 68-bus system demonstrate that, compared to traditional machine learning methods, the proposed joint loss with the spatiotemporal dynamic graph neural network model achieves higher accuracy in the identification of power system operational states, significantly improving classification performance on imbalanced samples with a 4.8% increase in F1-score, reaching a peak F1-score of 98.6%.

关键词： Training Adaptation models Accuracy power system dynamics power system stability Graph neural networks Stability analysis

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Extraction Steam Flow-generator power Modeling and Its Application in Wind power Consumption 5

Extraction Steam Flow-generator Power Modeling and Its Appli...

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5th International Conference on Energy, Electrical and power Engineering, CEEPE 2022

作者： Wen, Libin Hu, Hong Li, Jun Sun, Zhiyuan Zhang, Yihui Wu, Jianxu Electric Power Research Institute of Guangxi Power Grid Co. Ltd Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi Nanning China

ISBN: (纸本)9781665479059

Due to the randomness and volatility of wind power, the regulation capacity of power system is insufficient after large-scale grid connection. After the heating transformation of pure condensing thermal power unit, its regulating capacity has changed significantly. Therefore, the technical research of test and theoretical modeling is carried out. The minimum power value of the generator under steam extraction condition is tested through the test, and then the maximum output power value of the generator is obtained by considering the power loss caused by steam extraction. In this way, the steam extraction flow electric power model is obtained to calculate the regulating capacity in real time. According to the online visible regulation capacity, this can guide the stable operation of the power grid. This can be used for reference to promote the development of wind power. © 2022 IEEE.

关键词： Fluctuations Thermal engineering Heat engines Wind power generation Generators Regulation Real-time systems

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Short-Term Reactive Load Forecasting Based on a Hybrid Machine Learning Model

Short-Term Reactive Load Forecasting Based on a Hybrid Machi...

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2022 power System and Green Energy Conference, PSGEC 2022

作者： Qi, Le Chen, Mingyuan Song, Jifeng Zhang, Minyu Zheng, Wenbin Shang, Qinghua Power Dispatching Control Center of Guangxi Power Grid Co. Ltd Nanning China Guangxi University Key Laboratory of Guangxi Electric Power System Optimization and Energy-Savig Technology Nanning China

ISBN: (数字)9781665499934

ISBN: (纸本)9781665499934

With the improvement of people's living standards and the access to new energy sources such as rooftop photovoltaics, the variety of electricity consumption on the customer side has increased dramatically, placing high demands on the reactive power compensation configuration, regulation, and control capabilities at all levels of the distribution network. Predicting reactive loads directly impacts the quality of power supply and is also an integral part of reactive power optimization in the grid. With the popularity of smart energy measurement devices, large-scale historical reactive load data is uploaded to the dispatch control system. This paper proposes a hybrid reactive load prediction model based on a machine learning framework. Appropriate error parameters are selected, and the model is compared with a traditional time series prediction model to verify that the model can achieve better prediction results. © 2022 IEEE.

关键词： Machine learning

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