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arXiv 2024年

作者： Arjomandi-Nezhad, Ali Guo, Yifei Pal, Bikash C. Yang, Guangya The Department of Electrical and Electronics Engineering Imperial College London LondonSW7 2AZ United Kingdom The Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan250061 China The Department of Wind and Energy Systems The Technical University of Denmark Anker Engelunds Vej 1 Bygning 101A Kongens Lyngby2800 Denmark

When grid-forming (GFM) inverter-based resources (IBRs) face severe grid disturbances (e.g., short-circuit faults), the current limitation mechanism may be triggered. Consequently, the GFM IBRs enter the current-saturation mode, inducing nonlinear dynamical behaviors and posing great challenges to the post-disturbance transient angle stability. This paper presents a systematic study to reveal the fault recovery behaviors of a GFM IBR and identify the risk of instability. A closed-form expression for the necessary condition that a GFM IBR returns from the current-saturation mode to the normal operation mode is presented. Based on these analyses, it is inferred that the angle of the magnitude-saturated current significantly affects the post-fault recovery and transient stability;with different angle selection, the system may follow multiple post-fault trajectories depending on those conditions: 1) Convergence to a normal stable equilibrium point (SEP), 2) convergence to a saturated stable equilibrium point (satSEP), or 3) divergence (instability). In this paper, the circumstances under which a GFM IBR cannot escape from the current-saturation mode are thoroughly investigated. The theoretical analyses are verified by dynamic simulations. © 2024, CC BY.

关键词： Transient stability

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Analytical target cascading based real-time distributed voltage control for MV and LV active distribution networks

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2024年 159卷

作者： Jiao, Wenshu Wu, Qiuwei Chen, Jian Tan, Jin Song, Guocheng Huang, Sheng Wang, Chenshan Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Shanghai Univ Elect Power Coll Elect Engn Shanghai 200090 Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China

This paper proposes a new real-time distributed voltage control (RTDVC) scheme for medium and low voltage (MV &LV) distribution networks (DNs) based on the analytical target cascading (ATC) method. In this scheme, photovoltaic (PV) units at the LV level, on-load tap changer (OLTC) and distributed generation (DG) clusters at the MV level are optimally coordinated to regulate the bus voltages in MV &LV DNs to be close to the nominal value while minimizing the number of operations of OLTC and smoothing the reactive power outputs of DGs. Based on the ATC method, the large-scale strongly coupled voltage control problem of MV &LV DNs is decomposed into several subproblems while guaranteeing the optimality of the primal voltage optimization problem. The decomposed subproblems are iteratively solved in parallel in the MV and LV controllers, which achieves optimal voltage control in a distributed manner and effectively reduces the computation burden. An MV &LV test system with two 20 kV feeders and 39 0.4 kV LV grids was simulated to demonstrate the control performance of the proposed distributed voltage control scheme.

关键词： Analytical target cascading (ATC) distributed generation (DG) distribution network (DN) Reactive power control Voltage control

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The impact of DG's location on the small signal stability of the distribution network

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IOP Conference Series: Earth and Environmental Science 2019年第4期227卷

作者： Shaohui Zhang Wei Bao Jiadong Xu Xueshan Han Mingqiang Wang Yuehao Yan Xiaoyong Fu State Grid Zhengzhou Power Supply Company Zhengzhou China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University) Jinan China.

The distribution network has been integrated with more and more distributed generations. Most of these generations are inverter based photo-voltaic plant or DFIG based wind farm. As the proportion of these renewable energies goes high, the stability problems, especially the small signal stability problems gain attention from researchers. Literatures have conducted on the single machine infinite bus system of them, focusing mostly on their dynamic characteristics. This paper analyses the impact of DG's location on the small signal stability of the distribution network, which includes DGs, network and dynamic load. The conclusion is drawn from the modal analysis, and is verified by time domain simulation.

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Unit Commitment Considering Demand Response Behavior Based on Utility Maximization

Unit Commitment Considering Demand Response Behavior Based o...

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IEEE Conference on Energy Internet and Energy system Integration

作者： Yumin Zhang Xueshan Han Bo Xu Li Zhang Donglei Sun Xiaofeng Miao Jiayin Jiang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Economic & Technology Research Institute of State Grid Shandong Electric Power Company State Grid Shandong Electric Power Company Yantai Electric Power Company

ISBN: (纸本)9781538614280

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method.

关键词： Demand utility Decomposition coordination Electricity market Lagrangian relaxation Real-time pricing Unit commitment

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Dynamic reconfiguration of active distribution network considering multiple active management strategies

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IOP Conference Series: Earth and Environmental Science 2019年第3期227卷

作者： Wei Bao Shaohui Zhang Yichen Song Mingqiang Wang Xiao Li Yuehao Yan Xiaoyong Fu State Grid Zhengzhou Power Supply Company Zhengzhou China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University) Jinan China.

To make full use of various active management resources in ADN to improve the economic efficiency, a dynamic reconfiguration model of active distribution network considering multiple active management (AM) strategies is proposed in this paper. The AM strategies including the configuration of energy storage system, output power controlling of distributed generation, reactive power compensation with static var compensators and packet capacitor switching, tap adjusting with on-load tap changer, and demand side response management. The model tries to minimize the total costs with respect to various operating constraints. Several linearization techniques are applied to formulate the dynamic reconfiguration problem into a mixed-integer linear programming (MILP) model, which guarantees global optimal solution and also reduces the computational difficulty significantly. Finally, the validity and effectiveness of the proposed dynamic reconfiguration model is verified on the IEEE 33-node distribution network system.

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Enhancing power system Stability: A Machine Learning Approach with SVM, Random Forest and Deep Learning Utilizing Wide Area Measurements

Enhancing Power System Stability: A Machine Learning Approac...

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IEEE Student Conference on Electric Machines and systems

作者： Chao Song Mengcan Tan Mingzhao Chu Chihan Zhou Guojie Tian Longfei Mu Shandong Future Intelligent Technology Co. Ltd Shandong Electrical Engineering & Equipment Group Co. Ltd Jinan China Fengtai Supply Company Distribution Operation and Maintenance Center State Grid Beijing Electric Power Company Beijing China Changyi Supply Company Marketing Department State Grid Shandong Electric Power Company Changyi China State Grid Kunming Power Supply Company Kunming China Shandong Tianyu Changtong Energy Group Co. Ltd. Qingdao 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 the scale and complexity of modern power systems continue to expand, the importance of system stability has become increasingly critical. To ensure the stable operation of the power system, this paper proposes a power system stability analysis and optimal control strategy based on the Wide Area Measurement system (WAMS). Initially, a novel stability evaluation method is established using WAMS data and machine learning techniques, enabling effective handling of complex power system data and providing accurate stability assessments. Following this, an optimal control strategy is designed based on the evaluation method, aimed at real-time adjustments of power resource allocation to enhance system stability and responsiveness. Simulation analyses confirm the effectiveness and reliability of the proposed approach, indicating that the optimized control strategy significantly improves the system's performance under disturbances. This paper presents an innovative method for the stable operation of integrated power systems, contributing to the enhancement of power supply quality within the grid and ensuring the safe and efficient operation of the overall power system.

关键词： Time-frequency analysis system performance Optimal control power system stability system recovery Stability analysis Real-time systems Wide area measurements Voltage control Thermal stability

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A Data-Physics Fusion-Based Approach to power system Equivalent Inertia Assessment

A Data-Physics Fusion-Based Approach to Power System Equival...

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IEEE Student Conference on Electric Machines and systems

作者： Chihan Zhou Changtao Kan Gengkun Li Pengming Zhai Guojie Tian Shuang Liang Shuolin Zhang State Grid Kunming Power Supply Company Kunming China State Grid Jinan Power Supply Company Jinan China State Grid Zhejiang Electric Power Co. Ltd. Lishui Supply Branch Lishui China Wenshan Power Supply Bureau of Yunnan Power Grid Co. Ltd. Grid Metering Center of Yunnan Power Grid Co. Ltd. Wenshan China Shandong Tianyu Changtong Energy Group Co. Ltd. Qingdao 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

In order to solve the error problem of the traditional inertia assessment method, a power system equivalent inertia assessment method incorporating machine learning technology is proposed. First, a physical model of single-machine equivalence is used, combined with a convolutional neural network (CNN) with self-adaptive and learning capabilities as a machine learning model. Second, the strongly correlated feature quantities are selected as inputs by analyzing the model structure and calculating the correlation between the inertia time constant and other feature quantities. In addition, the computational results of traditional evaluation methods are incorporated into the data model inputs, and the model parameters are optimized using the particle swarm optimization (PSO) algorithm. The simulation results prove that the proposed method has certain advantages in improving the accuracy of inertia estimation compared with the traditional method.

关键词： Training Accuracy Computational modeling Estimation Machine learning power system stability Data models Stability analysis Convolutional neural networks Particle swarm optimization

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On the Use of Real-Time Transformer Temperature Estimation for Improving Transformer Operational Tripping Schemes

SSRN

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SSRN 2022年

作者： Cong, Yuhang Wall, Peter Osborne, Mark Li, Qi Li, Yigui Terzija, Vladimir School of Electrical and Electronic Engineering The University of Manchester ManchesterM13 9PL United Kingdom Electricity National Control Centre National Grid Berkshire RG41 5BN United Kingdom Chongqing University 174 Shazheng Road Shapingba District Chongqing400044 China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

During each summer, the super grid transformers (SGTs) inside GB transmission network are maintained according to the schedule which is determined by the asset management strategies. The outage of selected transformer often results in an increased loading on the rest of transformers in the adjacent circuits. Any type of faults occurring on circuits or other elements during this period of time is likely to cause overloads on the remaining transformers which could lead to a breach of the Security and Quality of Supply Standards (SQSS). The transformer operational tripping scheme (OTS) is a technique for protecting transformers from overloading by tripping pre-selected groups of generations so that the loading on the monitored transformers can be relieved during the contingencies. An event-based transformer OTS has been constantly armed in the GB network. This paper presents a novel technique to integrate the real time transformer temperature estimation into an existing transformer OTS. This technique improves the OTS by reducing the number of unnecessary generation tripping, which is initiated from the overly conservative transformer ratings. This novel scheme will generate enormous economic benefits as well as provide significant flexibility to the GB system operator – National Grid Electricity system Operator (NGESO). The new scheme is an example of a Wide Area Monitoring, Protection and control (WAMPAC) application. © 2022, The Authors. All rights reserved.

关键词： Temperature distribution

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A method of power grid partition based on influence law of component reliability

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IOP Conference Series: Earth and Environmental Science 2019年第5期233卷

作者： Wenzhu Zhang Yong Wang Ying Ding Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University) Jinan China State Grid of China Technology College Jinan China

In view of the increasing scale of power network and the complexity of reliability calculation, how to divide large power grid to reduce computational complexity is an urgent problem to be solved. In this paper, a partition method based on the rule of reliability influence between components is proposed to judge the area division of power network. By calculating the influence of component outage on the reliability index of other components, we can analyse the strength of the system regional relation, and partition the power system at the weakly connected nodes to reduce the computational complexity of reliability. At the end of the paper, we use the IEEE-RTS79 system model to simulate and calculate. By analysing the data and comparing with the partition results of other algorithms, we can verify the rationality of the proposed method.

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The Delicate Analysis of Short–Term Load Forecasting

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IOP Conference Series: Materials Science and Engineering 2017年第1期199卷

作者： Changwei Song Yuan Zheng Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jiangxi Electric Power Company Jiujiang Electric Power Supply Company China

This paper proposes a new method for short-term load forecasting based on the similar day method, correlation coefficient and Fast Fourier Transform (FFT) to achieve the precision analysis of load variation from three aspects (typical day, correlation coefficient, spectral analysis) and three dimensions (time dimension, industry dimensions, the main factors influencing the load characteristic such as national policies, regional economic, holidays, electricity and so on). First, the branch algorithm one-class-SVM is adopted to selection the typical day. Second, correlation coefficient method is used to obtain the direction and strength of the linear relationship between two random variables, which can reflect the influence caused by the customer macro policy and the scale of production to the electricity price. Third, Fourier transform residual error correction model is proposed to reflect the nature of load extracting from the residual error. Finally, simulation result indicates the validity and engineering practicability of the proposed method.

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