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Intelligent power and systems (ICIPS), International Conference on

作者： Ying Huang Yuanhong Lu Yanjun Zhao Yufeng Hu Jie Zhang Haiping Guo State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

The fault transient characteristics of power grids have undergone a fundamental transformation as a consequence of the advent of hybrid scale access to power grids by new energy sources. Nevertheless, the existing stand-alone equivalent model is unable to accurately characterise the fault transient characteristics of the hybrid light-water-wind electric field/cluster. Furthermore, the simulation computation of the stand-alone equivalent model is considerable in scale and the simulation efficiency is low. This paper proposes a particle swarm neural network-based clustered equivalent modelling method for a light-water-wind hybrid electric field. Firstly, a transient model of the light-water-wind hybrid electric field is established, and the characteristic influence factors of faults are constructed through theoretical analysis. These include the distance between the light-water-wind hybrid electric field and the point of common coupling (PCC), the input of current limiting measures on the DC side, the light, the water speed, the wind speed, and the reactive power at the outlet. Subsequently, the Euclidean distance is calculated for the set of characteristic influencing factors, and the initial centre of clustering of wind turbines is extracted based on the improved maximum-minimum distance method. Ultimately, the clustering equivalent modelling is accomplished through the utilisation of the aforementioned feature influencing factors and the classification initial centre as the training set. The simulation results show that compared with the single-machine equivalent model, The simulation error has been reduced from the order of magnitude of 10-2 p.u. to the order of magnitude of 10-4 p.u., while the simulation efficiency of this method is has been reduced from the order of magnitude of 10-2 s to the order of magnitude of 10-4 s.

关键词： Adaptation models Reactive power power measurement Computational modeling Wind speed Robustness power grids Electric fields Transient analysis Particle swarm optimization

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Application of photoelastic effect for excitation signal detection and optimization in laser-induced pressure propagation method

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IEEE Transactions on Dielectrics and Electrical Insulation 2025年

作者： Qi, Tianrun Ren, Hanwen Gao, Haoyu Li, Qingmin He, Xinjun Wang, Jian North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China Tokyo City University Measurement and Electric Machine Control Laboratory Setagaya158-8557 Japan

The crucial factor for ensuring space charge measurement resolution and signal intensity with the laser-induced pressure propagation method is the exceptional excitation performance. This study proposes a new approach for detecting high-frequency pressure pulse signals using the photoelastic effect. Based on the constructed pressure pulse optical detection system, the excitation characteristics and space charge measurement signals are investigated under different electrode materials and laser parameters. The experimental findings demonstrate that the selection of the target material, optimization of laser energy and spot diameter can significantly enhance the measurement resolution and signal intensity. Further, an optimized excitation scheme for the LIPP measurement device is proposed. The optimal spatial resolution and signal intensity are achieved when utilizing graphene as the target with laser energy of 340 mJ and spot diameter of 10 mm. Furthermore, the outcomes of the space charge evolution under intense electric field confirm the efficacy of the excitation optimization approach. Ultimately, the pressure pulse properties and generation process under distinct mechanisms are elucidated by integrating the developed simulation model of laser-induced pressure pulse. This study can offer valuable insights into the design of excitation scheme and investigation of the pressure wave generation mechanism in the LIPP method. © 1994-2012 IEEE.

关键词： Photoelasticity

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Analysis and suppression of low-frequency oscillation of photovoltaic cells with inertia control

Analysis and suppression of low-frequency oscillation of pho...

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China International Electrical and Energy Conference (CIEEC)

作者： Zhenyang Wang Gangui Yan Yue Zhao Jili Peng Dazhong Wang Shuang Ren Dept. Ministry of Education Key Laboratory of Modern Power System Simulation control and Green Power Technology Northeast Electric Power University Jilin China Dept. State Grid Hengyang Power Supply Branch State Grid Hunan Power Supply Hunan China

Aiming at the problem of low-frequency oscillation when photovoltaic power generation is connected to weak AC system, a linearization model of photovoltaic power generation is established, which ignores current inner loop and considers inertia control. The influence of various leading factors on low-frequency oscillation modes of photovoltaic power generation is analyzed. Finally, a low-frequency oscillation stabilizer (SSDC) is designed according to the phase compensation method to suppress the low-frequency oscillation of power system. The results show that the increase of input power of DC capacitor and the decrease of proportional control parameters of DC voltage loop and PLL will lead to the decrease of system damping and stability. Finally, the electromagnetic simulation model of weak AC system with photovoltaic power generation is built on PSCAD/EMTDC platform, which verifies the validity of eigenvalue analysis results and SSDC.

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Research on Mapping Method Between Smart Energy and Intelligent Sensing Terminal

Research on Mapping Method Between Smart Energy and Intellig...

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2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022

作者： Liu, Siyang Mao, Yuxing Long, Yunfeng Pan, Jianyu Jiang, Tianyan Nie, Yongjie School of Electrical Engineering Chongqing University State Key Laboratory of Power Equipment & System Security and New Technology Chongqing China Electric Power Measurement Digitalization Control and Protection Yunnan Power Grid Co. Ltd. Yunnan Key Laboratory of Green Energy Yunnan Kunming China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

In the process of smart city construction, each city has its characteristics, so we should implement policies according to the city. Smart energy is an important cornerstone of smart city construction. This paper proposes a mapping method between smart energy and Intelligent Sensing Terminal. Firstly, a typical application scenario design of the smart city is proposed. Then, the smart city application scenario fitness calculation model is given combined with the analysis of macro and micro scenes. Finally, Intelligent Sensing Terminal and scene mapping mechanism are proposed by a new two-dimensional coding method. This method can quickly and effectively calculate the location to be arranged and the optimal number of devices, so as to reduce resource consumption and improve the quality of perceived data. © 2022 IEEE.

关键词： Smart city

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Based on the Scenario Set Generation Technology, the Shared Energy Storage Site Selection and Capacity Determination Problem Considering the Grid Constraints

Based on the Scenario Set Generation Technology, the Shared ...

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

作者： Xiaobiao Fu Jinyu Guo Baoju Li Cuiping Li Yao Wang Junhui Li Guanqun Zhang Xingxu Zhu Dispatching and Control Center State Grid Jilin Electric Power Co. Ltd Chang Chun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education(Northeast Electric Power University) Ji Lin China Power Science Research Institute State Grid Jilin Electric Power Co. Ltd Chang Chun China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

This paper addresses the shared energy storage siting and sizing problem, considering grid constraints based on scenario generation techniques. In the context of high penetration of renewable energy, the power system faces practical challenges such as increased uncertainty and scarcity of flexible resources. To tackle these issues, a two-layer optimization model is proposed in this study. It utilizes scenario generation techniques to obtain possible scenarios for renewable energy and load outputs, and incorporates grid constraints for economic dispatch. Through iterative optimization, an optimal shared energy storage siting and sizing solution that meets the requirements of the power grid is obtained. Additionally, the paper discusses the impact on the accommodation capacity of renewable energy and proposes countermeasures in system economic dispatch. However, there are still limitations in uncertainty estimation, energy storage planning, and investment cost calculations in this paper. Furthermore, further enhancement is needed in terms of quantification theories supporting the economic evaluation of shared energy storage siting and sizing. Overall, this research aims to provide an optimization approach for the shared energy storage siting and sizing problem, incorporating scenario generation techniques and grid constraints, to promote stable operation and economic development of power systems with high penetration of renewable energy.

关键词： Renewable energy sources Uncertainty Costs Optimization models Robustness Planning Scenario generation

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Probability Evaluation Method of Available Transfer Capability Considering Source-Load Side Uncertainty 4

Probability Evaluation Method of Available Transfer Capabili...

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

作者： Chen, Donghui Chen, Zhengping Fan, Haiwei Xu, Xialing Liu, Meng Chen, Yanbo North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China State Grid Fujian Electric Power Company State Grid Fujian Electric Power Dispatching and Control Center Fuzhou China Central China Branch of State Grid Corporation China Central China Electric Power Dispatching Control Sub-Center Wuhan China

ISBN: (数字)9781665480796

ISBN: (纸本)9781665480796

Large scale wind power integration and demand response has brought uncertainty to both source and load side of power system which brings new challenges to the evaluation of available transfer capability (ATC) of power system. In order to evaluate the ATC under source-load side uncertainty more accurately, a probability evaluation method of ATC considering source-load side uncertainty is proposed in this paper. Firstly, the source-load side uncertainty is characterized by Gaussian mixture model (GMM)-based method. Then the calculation of ATC and existing transfer commitments (ETC) is done by the optimal power flow (OPF)-based model which both source and load side uncertainty is taken into consideration, and to ensure a globally optimal solution, the model is transferred into a second-order conic programming (SOCP) model. Finally, the Monte-Carlo simulation is used to evaluate the probabilistic ATC, and the modified IEEE 30-bus system is used as an example to analyze the influence of source-load side uncertainty on the evaluation of ATC and verify the correctness and validity of the proposed method. © 2022 IEEE.

关键词： Second-order cone programming

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Ultra-Short-Term Wind power Interval Prediction Based on Fluctuating Process Partitioning and Quantile Regression Forest

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Sun, Yong Huang, Yutong Yang, Mao Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Jilin Electric Power Company Ltd. Changchun China

As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current interval prediction methods are still incomplete in terms of tapping into the physical variability of wind power, especially for the specific time scale of the ultra-short term. This paper therefore proposes a new framework for interval forecasting of ultra-short-term wind power that incorporates the power fluctuation process. Firstly, a fluctuating process of wind power series is defined and a Kalman-SOM method for clustering the fluctuating processes of wind power is constructed. Secondly, a quantile regression forest interval prediction model is constructed for multiple fluctuation processes for ultra-short-term time scales. Finally, the effectiveness of the overall framework is validated at a wind farm in Jilin Province, China. Compared with the traditional interval prediction method. The interval bandwidth is reduced by 0.86% on average, and the interval coverage is increased by 1.4% on average. The results demonstrate the effectiveness and feasibility of the method in this paper.

关键词： wind power ultra-short-term prediction self-organizing map fluctuation quantile regression forest

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Non-unit protection for HVDC grids based on wavelet analysis of transient voltage

Non-unit protection for HVDC grids based on wavelet analysis...

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18th International Conference on Developments in power system Protection (DPSP APAC 2025)

作者： Xinyuan Li Boliang Jin Zhenkang Qi Binshu Chen Xinzhou Dong State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing People's Republic of China

ISBN: (数字)9781837242900

DC grids utilizing MMC-HVDC technology have been extensively researched and implemented in various locations, demonstrating substantial benefits in terms of system flexibility and renewable energy integration. Due to the rapid escalation of fault currents, DC line protections must quickly identify and isolate faults, typically within milliseconds, leading to the adoption of non-unit methods as the primary protection. This paper introduces a non-unit protection scheme that employs transient voltage at both the line-side and converter-side of the supplemental inductor. Based on a reduced model focusing on the boundary of a DC line, the transient process of the fault is examined using traveling wave theory, and the voltage characteristics at both ends of the supplemental inductor are scrutinized. The theoretical analysis also brings out a practical method for threshold-value calculation. Then, a protection criterion, based on wavelet analysis of the transient voltage, is established. This proposed method is capable of fulfilling the requirements for speed, selectivity and fault resistance and has been verified through PSCAD/EMTDC simulations.

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Forecasting-Aided Voltage Estimation for Distribution Network Considering the Integrated Management of Virtual power Plants Platform

Forecasting-Aided Voltage Estimation for Distribution Networ...

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IEEE Student Conference on Electric Machines and systems

作者： Yujian Jia Zhao Liu Changtao Kan Yue Yu Changgang Li State Grid Jinan Power Supply Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

As more distributed energy sources integrate into distribution networks, issues such as voltage fluctuations and reduced observability become increasingly prominent. Therefore, this paper proposes an algorithm for forecasting-aided state estimation (FASE) in virtual power plants' integrated operation management platform. Firstly, a Bidirectional Long Short-Term Memory (BiLSTM)-Extended Kalman Filter (EKF) algorithm for distribution network FASE is introduced. Secondly, the integrated management of virtual power plant platforms (IM-VPPP) enhances the observability of distribution networks. To evaluate the performance of the proposed method, simulations are conducted using the IEEE 33-bus standard distribution system. Results demonstrate significant advantages of the algorithm in terms of accuracy and robustness.

关键词： Voltage measurement Voltage fluctuations Noise Distribution networks Virtual power plants Robustness Kalman filters state estimation Observability Standards

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Long-Foresight-Term power Prediction Considering the Evolution of Significant Weather Information for Wind Farm Cluster

SSRN

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SSRN 2023年

作者： Yang, Mao Jiang, Renxian Zhang, Xiaobin Huang, Yutong Guo, Yunfeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Grid Gansu Electric Power Company Gansu730030 China

The current wind power prediction horizon extends up to 7 days, and the research on power prediction for the 8 to 15 day-ahead is still lacking. However, with the increasing proportion of renewable energy in novel power systems, breaking through the long-foresight-term power prediction barrier is crucial support for guaranteeing the secure and stable operation of the power system. To address the aforementioned issues, this study presents a power prediction method for wind farm cluster (WFC) in long-foresight-term, based on the poor availability of existing numerical weather prediction (NWP) in long-foresight-term. Firstly, a significant wind process identification method considering autocorrelation analysis is employed to predict future power trends, and an optimal method is explored for power generation (PG) prediction in the 8 to 15 day-ahead. Secondly, under the constraint of predicted PG, the power corresponding to the historical similar wind process is selected as the predicted value. Finally, the proposed methodology is applied to a WFC in Gansu Province, China. The results indicate that the proposed method reduces the average RMSE and MAE by 4.15% and 3.3%, respectively, effectively tracking the changing trends of wind power. Moreover, it achieves long-foresight-term prediction and enhances the reliability of the prediction. © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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