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IEEE International Conference on power and Energy Applications (ICPEA)

作者： Xiyang Liu Tianhao Liu Yutian Liu Zhendong Li Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Laiwu Power Supply Company State Grid Shandong Electric Power Company Laiwu China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

The continuous increase of new energy generation and AC-DC interconnection make the transient voltage stability of the receiving-end power grid more and more complicated. In order to realize the rapid assessment of transient voltage stability, a one-dimensional Convolutional Neutral Network (CNN) for transient voltage stability assessment (TVSA) is constructed by selecting the features reasonably on the basis of using the Agglomerative Hierarchical Clustering (AHC) algorithm to partition the receiving-end grid. In order to enhance the assessment work, the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm is utilized to find out the concerns of the model to features, and the model knowledge of the neural network is analyzed on the basis of surveying on a large number of samples. Based on the transient voltage stability mechanism and the concerns of deep learning model, the factors that cause transient voltage instability are analyzed. The effectiveness of the proposed method is demonstrated by the case study of a provincial grid in eastern China.

关键词： Knowledge engineering Analytical models Voltage power system stability Stability analysis power grids Partitioning algorithms Convolutional neural networks Transient analysis Voltage control

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Nonlinearity Characteristic of High Impedance Fault at Resonant Distribution Networks: Theoretical Basis to Identify the Faulty Feeder

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IEEE TRANSACTIONS ON power DELIVERY 2022年第2期37卷 923-936页

作者： Wei, Mingjie Zhang, Hengxu Shi, Fang Chen, Weijiang Terzija, Vladimir Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China State Grid Corp China Beijing 100031 Peoples R China Skolkovo Inst Sci & Technol Ctr Energy Sci & Technol Moscow 143026 Russia

Feeder identification is indispensable for distribution networks to locate faults at a specific feeder, especially when measuring devices are insufficient to locate faults more precisely. For the high impedance fault (HIF), the feeder identification is much more challengeable and related approaches are still in the early stage. This paper thoroughly reveals the nonlinearity characteristics of different feeders when a HIF happens at a three-wire system that is with the resonant grounded neutral (RGN). Firstly, the diversity of nonlinearity existing in HIFs is explained from the perspective of energy. Then, the nonlinearity of zero-sequence current that differs between healthy and faulty feeders are deduced theoretically. Effects of the detuning index of Petersen coil, the damping ratio of system, and the length of feeder are all considered. Afterward, these theoretical conclusions are verified by the HIF cases experimented in a real 10kV system. Finally, after indicating the problems of a classic phase-relationship-based algorithm, we suggest an improved method based on the phase differences between the harmonic currents of different feeders. The effectiveness of the method has been verified.

关键词： Distortion Fault diagnosis Harmonic analysis Impedance Distribution networks Substations Transient analysis Distribution networks feeder identification high impedance fault nonlinearity resonant grounded neutral three-wire system

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The Optimization Method for key control Parameters of Wind Turbines to Suppress Transient Overvoltage in Wind-Fire Bundling AC/DC power Delivery system

The Optimization Method for Key Control Parameters of Wind T...

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intelligent power and systems (ICIPS), International Conference on

作者： Zhuohang Liang Wuneng Ling Chengxiang Li Zhencheng Liang Li Xiong Yangdou Liang Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Electric Power Research Institute China Southern Power Grid Guangzhou China Guangxi Power Grid Dispatch and Control Center Nanning China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

This paper analyzes the causes of overvoltage in the sending-end grid due to phase-change failures in the receiving-end grid, based on the operational principles and control methods of conventional high-voltage DC transmission. It systematically examines the operational characteristics of the sending-end grid voltage during transient processes. Considering the control strategy and output power expression of direct-drive wind turbines connected to the grid, and in accordance with current control requirements for voltage transients in wind turbine units, the study identifies parameter values affecting the control performance of voltage transients. It proposes a key control parameter optimization model aimed at minimizing fluctuations in the terminal voltage of wind turbines during voltage faults, integrating a simulated annealing optimization algorithm. Detailed implementation steps for optimizing key parameters are provided. Finally, the effectiveness of the proposed method in suppressing overvoltages at the terminal of wind turbines is validated using a model built on an electromechanical transient simulation platform.

关键词： Optimization models Process control Switches Simulated annealing power system stability control systems Wind turbines Voltage control Transient analysis power generation

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Extension of power Flow Algorithm in STEPS for AC/DC Hybrid power systems with VSC-MTDC

Extension of Power Flow Algorithm in STEPS for AC/DC Hybrid ...

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IEEE IAS Conference on Industrial and Commercial power system Asia (IEEE I and CPS Asia)

作者： Ma, Zhenhe Li, Changgang Ye, Hua Liu, Yutian Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9781665434980

The open-source simulation toolkit for electrical power systems (STEPS) was released in Github with power flow and dynamic simulation functions. However, voltage source converter based multi-terminal direct current (VSC-MTDC) was not supported in STEPS. In this paper, the steady-state model of VSC-MTDC is introduced with diverse control modes. Then, the AC/DC power flow algorithm with VSC-MTDC is designed with alternating iteration method. The controlled variables exceeding limits with different control modes are handled in the algorithm. Besides, a general data structure of VSC-MTDC is established based on PSS/E and realized in STEPS. Finally, Two cases with VSC-MTDC are tested to verify the feasibility and effectiveness of the designed algorithm.

关键词： voltage source converter AC/DC system power flow calculation STEPS

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A Practical Reference Network Planning Model Based on Load Moment and Acceptable Range

A Practical Reference Network Planning Model Based on Load M...

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

作者： Jianjie Li Wentao Zhong Mingliang Mu Jialiang Wang State Grid Shandong Province Power Company Binzhou Power Supply Company Binzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

There is a big gap between theoretical research and practical application of reference network planning. Most of the existing planning models in academic research take cost as the objective function. Although various advanced models and methods are proposed based on this, they are rarely applied in actual power companies. In this paper, a new reference network planning model is proposed according to the actual demand. According to the field investigation, "power supply to the nearest load" is taken as the goal, and the load moment is expressed analytically. In order to meet the increasing demand of renewable energy integrating into the power grid, the concept of acceptable disturbance range is added to the model constraint to improve the system's absorption capacity of renewable energy. Finally, the N-1 security constraint is considered to improve the reliability of the model. The model is transformed into a mixed integer linear programming (MILP)problem by priority objective programming method and can be solved with mature commercial solvers. The validity of the model is verified by IEEE-RTS24 node system. When N-1 safety constraints are taken into account, the advantages of the proposed model become apparent, with a total cost reduction of about 2.5%.

关键词： Renewable energy sources Costs power supplies Biological system modeling Programming Minimization Planning

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A Bayesian Structural Time Series Approach for Forecasting Photovoltaic power Generation

A Bayesian Structural Time Series Approach for Forecasting P...

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International Conference on power system Technology (powerCON)

作者： Chenghao Sun Xiaodong Chu Hua Ye Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan P.R. China

As a renewable energy source, photovoltaic (PV) power generation is becoming increasingly essential in power systems. Accurate forecasting of PV power output is crucial for effective regulation and control of these systems. This paper explores the applicability of the Bayesian structural time series model for PV power generation forecasting using causal inference techniques. The research examines various factors that influence PV power generation and assesses their causal relationships. The developed forecasting model for PV power generation integrates the Bayesian structural time series approach. The accuracy of the proposed model is validated through case studies, demonstrating the successful incorporation of causal inference in PV power generation prediction. This study lays the foundation for future research on utilizing causal inference to evaluate the impacts of specific system changes.

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Study on Capacity Ratio Optimization of Multi-Energy power system 5

Study on Capacity Ratio Optimization of Multi-Energy Power S...

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

作者： Li, Wensheng Yang, Bin Yuan, Zhenhua Huang, Dan Cheng, Peifen Yun, Jiangyang State Grid Shandong Electric Power Company Economic & Technology Research Institute Jinan China China Electric Power Research Institute Beijing China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9781665479059

In order to achieve the goal of "double carbon", it is urgent to build a new power system with new energy as the main body. It is vital for the construction and planning of new power system to reasonably optimize the installed ratio of various power supplies. To this end, this paper proposes a capacity allocation optimization method of multi energy power system based on complementary equilibrium theory, and establishes the capacity optimization models of multi-energy system such as wind power, thermal power, nuclear power and energy storage with the objective of minimizing the operation cost of the whole network. The model adopts the load characteristics, the output characteristics of new energy and the operation characteristics of energy storage power stations in the target power grid. The annual output time series of wind/photovoltaic and the load series are used as the input of the model. Through the annual time series production simulation calculation, the optimal capacity ratio of wind-photovoltaic-thermal-nuclear-storage system is determined to meet the conditions. Finally, a regional power grid in China is demonstrated as an example to verify the effectiveness and practicability of the proposed model and method. © 2022 IEEE.

关键词： Costs Time series analysis Optimization methods Production power grids power systems Planning

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Variable DC-Link Voltage Regulation of Single-Phase MMC Battery Energy-Storage system for Reducing Additional Charge Throughput

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IEEE TRANSACTIONS ON power ELECTRONICS 2021年第12期36卷 14267-14281页

作者： Ma, Zhan Gao, Feng Zhang, Chenghui Li, Wei Niu, Decun Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

Battery energy-storage system (BESS) based on the modular multilevel converter (MMC) can flexibly manage the battery packs integrated into submodules, where the battery pack can directly or through a small capacitor connect to the rear-end half-bridge circuit for reducing cost and volume caused by an additional dc-dc converter. But the alternating current ripples will cause substantial additional charge throughput for battery packs and, consequently, reduce the battery lifetime in theory. Therefore, this article proposes a variable dc-link voltage regulation method for a single-phase MMC-BESS. In specific, the phase disposition (PD) modulation scheme is improved to properly bypass the gating signals with unnecessary conduction during operation and the modified gating signals will be rearranged for balancing the states-of-charge and states-of-health. Doing so, the additional charge throughput could be significantly reduced compared with the traditional phase-shift modulation and PD modulation. Even comparing with the ideal dc current charging/discharging, the proposed method will only increase slight additional charge throughput and nearly negligible capacity loss. The experimental results of a 6.6 kW/6.6 kWh single-phase MMC-BESS prototype verified the performance of the proposed method.

关键词： Batteries Throughput Aging Frequency modulation Capacitors Voltage control Partial discharges Battery energy-storage system (BESS) charge throughput dc-link voltage modular multilevel converter (MMC)

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Topology Identification in LV Distribution Network Based on SAE and Modified DBSCAN

Topology Identification in LV Distribution Network Based on ...

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58th IEEE/IAS Industrial and Commercial power systems Technical Conference Asia (IEEE I and CPS Asia)

作者： Miao, Xiaowei Yuan, Jianhua Yang, Ming Ou, Zhujian Huang, Dongdong Mao, Yifeng Liu, Wangchun Cao, Yue State Grid Jiangsu Elect Power Co Ltd State Grid Nantong Power Supply Co Nantong Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Shandong Peoples R China

ISBN: (数字)9781665450669

ISBN: (纸本)9781665450669

The mistakes in topology records of low voltage distribution network influence the economic operation of the power grid. However, most existing methods to detect the customers who do not match the records are not always reliable and can't realize automatic identification. This paper proposes an identification method based on stacked autoencoder (SAE) and modified Density-Based Spatial Clustering of Applications with Noise (DBSCAN). SAE is applied to reduce the data dimensions and extract nonlinear feature vectors from voltage time series. The modified DBSCAN can adjust parameters adaptively and cluster the feature vectors to identify the customers with wrong transformer connectivity, which improves the automation management level in distribution network. Case studies on real datasets have verified that the proposed method has high identification accuracy.

关键词： Distribution network topology SAE DBSCAN transformer connectivity

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Short-Term Load Forecastiong Based on Residual Graph Convolutional Neural Network

Short-Term Load Forecastiong Based on Residual Graph Convolu...

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International Conference on power system Technology (powerCON)

作者： Mengqing Bian Xiaodong Chu Hua Ye Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan P.R. China

As various industries experiencing post-pandemic economic recovery, power systems face increased challenges. Short-term power load forecasting for regional power grids can assist in anticipating load fluctuations and optimizing power system management planning. This paper tackles the gradient vanishing issue in deep graph convolutional neural networks (GCNs) by incorporating a residual module to create a residual graph convolutional neural network (ResGCN). Data from a regional power grid in the United States is utilized for validation purposes. Experimental results show that the graph convolutional neural network with the residual module generates predictions closer to the actual values, consequently enhancing prediction accuracy and confirming the efficacy of the proposed ResGCN.

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