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检索条件"机构=Key Laboratory of Intelligent Dispatching and Control of Power Grid"

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Research on Automatic Generation control Technology for New Energy grid Connection

Research on Automatic Generation Control Technology for New ...

引用

power Science and Technology (ICPST), IEEE International Conference on

作者： Li Xiong Qiuquan Deng Ling Li Yangdou Liang Ye Zhang Wei Liu Power Dispatching and Control Center Guangxi Power Grid Co. Ltd. Nanning China Nanning Electric Power Supply Bureau Guangxi Power Grid Co. Ltd. Nanning China State Key Laboratory of HVDC (Electric Power Research Institute China Southern Power Grid) Guangzhou China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

The power industry takes the lead to achieve its carbon peak and carbon neutrality targets. The construction of the new power system with new energy as the main body is of great significance to the realization of the "dual carbon" goal. Nonetheless, the substantial integration of renewable energy sources into the power grid is anticipated to induce considerable disruptions, while conventional control techniques struggle to mitigate challenges like frequency disparities and poor CPS performance. Based on this problem, from the standpoint of automatic generation control, this paper proposes an automatic generation control algorithm for new energy grid-connected, that is, Self-Adaptive Reinforcement Exploration Double Speedy Q-learning algorithm(SARE-DSQL). The presented algorithm incorporates a self-adaptive reinforcement exploration approach into Speedy Q-learning to effectively balance exploration and exploitation. Additionally, it integrates the Double Q-learning strategy to address the issue of action exploration value overestimation within the Q algorithm framework, thereby enhancing algorithm convergence and update efficiency. Our study conducts simulations using the enhanced IEEE standard two-area load frequency control model to assess the efficacy of the proposed algorithm.

关键词： Renewable energy sources Q-learning Automatic generation control power industry power grids Indexes Carbon

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A Coordinated control Method for Wind Farm-Energy Storage Joint Systems Participating in Frequency Regulation

A Coordinated Control Method for Wind Farm-Energy Storage Jo...

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power Energy Systems and Applications (ICoPESA), International Conference on

作者： Yingjie Qin Yu Liu Lu Miao Jinchang Chen Yingxuan Sun Ping Yang Power Dispatching and Control Center System Analysis Department Guangdong Power Grid Corporation Guangzhou China Guangdong Key Laboratory of Clean Energy Technology South China University of Technology Guangzhou China

ISBN: (数字)9798350351668

ISBN: (纸本)9798350351675

With a substantial increase in wind power integration into the power grid, ensuring grid frequency stability faces significant challenges. This paper integrates the inherent frequency regulation mechanisms of wind power with energy storage technology to engage in power system frequency regulation. Through an analysis of the impact of wind power grid integration on power system frequency, the necessity of wind-storage joint participation in frequency regulation is elucidated, and a model for wind-storage joint system participation in power system frequency regulation is established. Furthermore, fuzzy control is employed for adjusting the virtual inertia response coefficient, with the energy storage system output controlled based on the state of charge (SOC) of the energy storage system. In the simulation process, analyses and comparisons are conducted between scenarios where wind power does not participate in frequency modulation (FM), wind power participates in FM under low wind speeds, and wind-storage jointly participates in FM under high wind speeds to validate the advantages of the wind-storage joint FM scheme. Additionally, comparisons are made between rotational speeds under fixed and variable coefficient scenarios, along with comparisons of load state and power supply, to verify the advantages of the wind-storage joint FM control strategy proposed in this paper.

关键词： Frequency modulation Wind speed Rotors Wind power generation power system stability Wind turbines State of charge Kinetic energy Frequency control Energy storage

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Prediction and Preventive control Scheme for Wind and PV power Ramp Events

Prediction and Preventive Control Scheme for Wind and PV Pow...

引用

IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Yifei Zhai Zengwei Wang Kunpeng Zhang Huan Ma Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Power Grid Technology Center State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

As the large scale integration of photovoltaic and wind power into the grid increases, renewable energy ramp events have become a potential threat to the secure operation of the power grid. To effectively address renewable energy power ramp events, this paper proposes a prediction and preventive control scheme. First, a rolling warning approach is achieved by the long short-term memory network and fuzzy logic, which provides warning levels and guides decision-making for preventive control. Second, a two-stage optimization scheduling model is proposed, including a day-ahead and an intra-day sub-model. The two-stage scheduling model comprehensively considers power support from interconnectors and preventive control costs. Simulation results demonstrate that the proposed scheme can provide adaptive preventive control strategies for power ramp events with varying risk levels, thereby enhancing the utilization of renewable energy and improving the security of power system.

关键词： Photovoltaic systems Renewable energy sources Adaptation models Costs Simulation Decision making power system stability Wind power generation Wind forecasting Transient analysis

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Temperature Characteristics Analysis of Transformer Cooling Systems Under Variable Loads and Inter-Turn Short-Circuit Faults

Temperature Characteristics Analysis of Transformer Cooling ...

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2023 International Conference on power System Technology, powerCon 2023

作者： Chen, Liangyuan Zhou, Ke Li, Dajian Zhao, Jian Gao, Xunbo Tong, Ruize Du, Houxian Electric Power Research Institute of Guangxi Power Grid Corporation Co. Ltd. Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi Zhuang Autonomous Region Nanning530023 China Electric Power Research Institute of Guangxi Power Grid Corporation Co. Ltd. Guangxi Zhuang Autonomous Region Nanning530023 China Guangxi Power Grid Corporation Co. Ltd. Guangxi Zhuang Autonomous Region Nanning530023 China Digital Grid Research Institute of China Southern Power Grid Guangzhou510000 China

ISBN: (纸本)9798350300222

power transformers are essential components of the power system, and their safe and stable operation is of paramount importance. Temperature monitoring plays a vital role in transformer condition assessment, as it is crucial for preventing defects such as insulation aging caused by overheating. The cooling system, a critical part of transformer heat dissipation, indirectly reflects the internal temperature distribution of the transformer. In this paper, by analyzing the cooling system's heat dissipation methods, we establish simplified models for both the transformer body and the cooling system. We simulate the temperature distribution of the cooling system under different loads and various inter-turn short-circuit faults, summarizing their corresponding relationships with the load multiples. The results indicate that the cooling system's temperature distribution exhibits a 'higher on top, lower at bottom' pattern, showing a linear correlation with both the load multiples and the severity of inter-turn short-circuit faults. © 2023 IEEE.

关键词： Temperature distribution

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A Multi-Step Joint Q-learning Cooperative Algorithm for Regional Interconnected power Systems

A Multi-Step Joint Q-learning Cooperative Algorithm for Regi...

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power Science and Technology (ICPST), IEEE International Conference on

作者： Li Xiong Ling Li Wei Liu Zhencheng Liang Wuneng Ling Ye Zhang Power Dispatching and Control Center Guangxi Power Grid Co. Ltd. Nanning China Nanning Electric Power Supply Bureau Guangxi Power Grid Co. Ltd. Nanning China State Key Laboratory of HVDC (Electric Power Research Institute China Southern Power Grid) Guangzhou China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

Distributed renewable energy, due to its own randomness, intermittency and unpredictability, will lead to frequency fluctuations in the power system when it is connected to the grid on a large scale, posing a serious challenge to the security, stability and economy of the interconnected grid. This paper outlines a systematic strategy aimed at mitigating the adverse effects of strong random disturbances and frequency instability associated with the integration of new energy sources into the power grid. The approach centers on optimizing the Automatic Generation control (AGC) within a distributed multi-region multi-energy interconnection power system. Consider battery storage and conventional units, collaboratively involved in AGC frequency regulation, a novel time-difference algorithm DQ(σ, λ) is proposed, and the introduction of hybrid sampling factors unifies the Sarsa algorithm with the Expected-Sarsa algorithm to achieve the optimal solution of the optimal strategy, and then realize the optimal cooperative in distributed multi-region. The real grid environment is simulated by the constructed two-region interconnected power system model with energy storage and the distributed multi-region multi-energy synergy power system model in order to verify the practical engineering effectiveness of the DQ(σ, λ) algorithm. The results show that the DQ(σ, λ) algorithm has fast convergence characteristics, and is able to solve the frequency instability problem and obtain the optimal synergy among the regions of the power grid.

关键词： Renewable energy sources Systematics Q-learning Fluctuations Automatic generation control power system stability power grids

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An Operational Risk Prevention Strategy Based on Dynamic Line Rating

An Operational Risk Prevention Strategy Based on Dynamic Lin...

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IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Lingzi Zhu Jieling Li Mingshun Liu Liweiyong Guo Dongxu Chang Power Dispatching Control Center Guizhou Power Grid Co. Ltd Guiyang China Power Dispatching Control Center of Guizhou Power Grid Co. Ltd Guiyang China Department of Electric Power Engineering Chongqing University Chongqing China School of Electrical Engineering Chongqing University Chongqing China Electric Power Research Institute China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

As renewable energy becomes increasingly used, its uncertainty leads to a lack of initiative in power system prevention methods. Therefore, based on the application of Dynamic Line Rating (DLR), this paper proposes a new strategy for operational risk prevention in power systems under considerations of supply and demand uncertainties as well as DLR prediction. First of all, the probability density function and sequential expected power are utilized to describe the uncertainty models of wind power and load. Subsequently, a combination prediction model of DLR based on the entropy method is proposed to characterize the uncertainty of DLR. Finally, the DLR is applied in the risk assessment model. A risk index is proposed to describe the overload of the transmission line. The performance is tested in the IEEE-39 system, and the results show the prediction accuracy and risk prevention effectiveness of DLR.

关键词： Renewable energy sources Uncertainty Supply and demand Biological system modeling power system dynamics Predictive models Wind power generation

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Classification and aging assessment of kraft and thermally upgraded insulating paper via near-infrared spectroscopy

Classification and aging assessment of kraft and thermally u...

引用

IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Xinran Qin Lei Zhang Liangyuan Chen Rui Li Yuan Ma Guangxi Key Laboratory of Intelligent Control and Operation and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Guangxi China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

In recent years, researchers propose using near-infrared spectroscopy to achieve non-destructive aging assessment of insulating paper. However, different types of paper samples exhibit spectral differences, which require the consideration of complex and multiple mapping relationships during model training, leading to a conflict between the generalization ability and accuracy of the model. In this paper, a strategy combining paper sample classification with aging assessment has been adopted. Craft paper and thermally upgraded paper samples in different aging states are collected and analyzed. It is observed that the changes in NIR spectra and degree of polymerization (DP) varied among different types of paper samples. The disparities in NIR spectra between different paper types enabled the paper sample classification model based on random forest to achieve high accuracy. In addition, four single type DP prediction model based on partial least squares regression are developed. The validation on the test set demonstrated that our proposed models had lower root mean square error compared to hybrid model (73.8 vs 95.7).

关键词： Training Radio frequency Predictive models Aging Thermal analysis Polymers Functional near-infrared spectroscopy

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The application research of acoustic imaging technology in partial discharge detection at substations

The application research of acoustic imaging technology in p...

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power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Xia Xiaofei Su Yi Feng Bo Lu Yufeng Rao Xiajin Electric Power Research Institute of Guangxi Power Grid Co. Ltd Guangxi China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

Partial discharge is a major cause of failures in power station equipment. When partial discharge occurs during the operation of power equipment, it is usually accompanied by abnormal acoustic emissions. However, the operating environment of large power equipment is often filled with a significant amount of noise, making it challenging to accurately locate the abnormal sounds generated by partial discharge. In this study, acoustic imaging detection technology is employed to analyze the performance of various acoustic imaging algorithms. A 64-channel multi-arm spiral microphone array is designed with high dynamic range and resolution to intuitively depict partial discharge phenomena. The study combines acoustic imaging technology with visible light imaging technology, overlaying acoustic imaging and visible light video images transparently. Simultaneously, an analysis of the high-noise acoustic environment in the substation is conducted, filtering out noise present in the substation environment. Experimental testing of the acoustic imaging equipment is performed on-site at the substation, and the results indicate that the instrument can achieve real-time and accurate localization of abnormal acoustic emissions in the high-noise environment of the substation. Additionally, it can effectively identify abnormal acoustic emissions in different frequency bands, providing a powerful tool for early detection and prevention of power equipment failures.

关键词： Partial discharges Substations Acoustic imaging Software algorithms Noise Imaging Acoustic emission

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Partial Discharge Type Identification Based on PSO Optimised BP-RF Model and Multi-Type Sensors

Partial Discharge Type Identification Based on PSO Optimised...

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power and Electrical Engineering (ACPEE), 5th Asia Conference on

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

For the partial discharge phenomenon occurring during the use of power equipment, the partial discharge data acquired by multiple sensors (HFCT, AE, TEV) are used to correct the PRPD map by image processing techniques, so as to improve the accuracy of partial discharge type identification. The partial discharge signals under different experimental conditions were acquired using HFCT, AE and TEV sensors, and the alignment of PRPD images acquired by different sensors was achieved by image processing. On this basis, the data from individual sensors were preliminary classified using BP neural networks to identify different types of partial discharge patterns; the per-classification results of these individual sensing were input into the Random Forest algorithm model as features, while the Particle Swarm Optimization algorithm was used to search for the optimal hyper-parameters of the Random Forest, and finally, the Random Forest algorithm model of the Particle Swarm Optimization was used to make the final decision and classification. The experimental results show that the method can effectively identify and classify different types of partial discharges, providing a new technical way for power system maintenance and fault prevention.

关键词： Partial discharges Image sensors Image processing Neural networks Sensor phenomena and characterization Data models Classification algorithms

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Analysis of the Resource Potential of Electric Vehicles Participating in Vehicle-to-grid Interaction

Analysis of the Resource Potential of Electric Vehicles Part...

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Energy Systems and Electrical power (ICESEP), International Conference on

作者： Weidong Chen Ning Wu Jianbin Lu Shuai Han Xiaorui Wu Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning China

ISBN: (数字)9798350353563

ISBN: (纸本)9798350353570

The growing demand for charging significantly impacts the operation and dispatch of power systems with the continuous increase in the number of electric vehicles (EVs) and charging infrastructure. The importance of EVs participating in demand response is becoming increasingly apparent. Compared to other demand-side flexibility resources, EVs can provide more flexible and cost-effective demand response capabilities. Guiding and managing EV participation in ancillary services of the power system aids in ensuring grid security and promoting the integration of new energy sources. This paper calculates the significant potential of EVs participating in grid frequency regulation, expecting to become an essential supplement to power system dispatch and promote the broader application of clean energy.

关键词： Warranties Vehicle-to-grid Electric potential Stability criteria power system stability Demand response Batteries

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