Journal of Modern Power Systems and Clean Energy最新文献_第8页

High-Impedance Fault Section Location for Distribution Networks Based on T-Distributed Stochastic Neighbor Embedding and Variable Mode Decomposition 基于 T 分布随机邻域嵌入和可变模式分解的配电网络高阻抗故障段定位

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-12-05 DOI: 10.35833/MPCE.2023.000225

Zhihua Yin;Yuping Zheng;Zhinong Wei;Guoqiang Sun;Sheng Chen;Haixiang Zang

{"title":"High-Impedance Fault Section Location for Distribution Networks Based on T-Distributed Stochastic Neighbor Embedding and Variable Mode Decomposition","authors":"Zhihua Yin;Yuping Zheng;Zhinong Wei;Guoqiang Sun;Sheng Chen;Haixiang Zang","doi":"10.35833/MPCE.2023.000225","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000225","url":null,"abstract":"When high-impedance faults (HIFs) occur in resonant grounded distribution networks, the current that flows is extremely weak, and the noise interference caused by the distribution network operation and the sampling error of the measurement devices further masks the fault characteristics. Consequently, locating a fault section with high sensitivity is difficult. Unlike existing technologies, this study presents a novel fault feature identification framework that addresses this issue. The framework includes three key steps: ① utilizing the variable mode decomposition (VMD) method to denoise the fault transient zero-sequence current (TZSC); ② employing a manifold learning algorithm based on t-distributed stochastic neighbor embedding (t-SNE) to further reduce the redundant information of the TZSC after denoising and to visualize fault information in high-dimensional 2D space; and ③ classifying the signal of each measurement point based on the fuzzy clustering method and combining the network topology structure to determine the fault section location. Numerical simulations and field testing confirm that the proposed method accurately detects the fault location, even under the influence of strong noise interference.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10345458","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation 基于深度神经网络的时间同步配电系统状态估计性能的分析验证

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-12-05 DOI: 10.35833/MPCE.2023.000432

Behrouz Azimian;Shiva Moshtagh;Anamitra Pal;Shanshan Ma

引用次数: 0

An Adaptive Data-Driven Method Based on Fuzzy Logic for Determining Power System Voltage Status 基于模糊逻辑的自适应数据驱动方法用于确定电力系统电压状态

IF 6.3 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-12-05 DOI: 10.35833/MPCE.2023.000325

Sirwan Shazdeh;Hêmin Golpîra;Hassan Bevrani

引用次数: 0

Temporal and Spatial Optimization for 5G Base Station Groups in Distribution Networks 分布式网络中 5G 基站群的时空优化

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-29 DOI: 10.35833/MPCE.2023.000024

Silu Zhang;Nian Liu;Jianpei Han

{"title":"Temporal and Spatial Optimization for 5G Base Station Groups in Distribution Networks","authors":"Silu Zhang;Nian Liu;Jianpei Han","doi":"10.35833/MPCE.2023.000024","DOIUrl":"10.35833/MPCE.2023.000024","url":null,"abstract":"With the large-scale connection of 5G base stations (BSs) to the distribution networks (DNs), 5G BSs are utilized as flexible loads to participate in the peak load regulation, where the BSs can be divided into base station groups (BSGs) to realize inter-district energy transfer. A Stackelberg game-based optimization framework is proposed, where the distribution network operator (DNO) works as a leader with dynamic pricing for multi-BSGs; while BSGs serve as followers with the ability of demand response to adjust their charging and discharging strategies in temporal dimension and load migration strategy in spatial dimension. Subsequently, the presence and uniqueness of the Stackelberg equilibrium (SE) are provided. Moreover, differential evolution is adopted to reach the SE and the optimization problem in multi-BSGs is decomposed to solve the time-space coupling. Finally, through simulation of a practical system, the results show that the DNO operation profit is increased via cutting down the peak load and the operation costs for multi-BSGs are reduced, which reaches a win-win effect.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10335160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141769490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data 基于经验小波变换的方法，利用 PMU 数据识别和分析次同步振荡模式

IF 6.3 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-29 DOI: 10.35833/MPCE.2023.000047

Joice G. Philip;Jaesung Jung;Ahmet Onen

引用次数: 0

Parameter Estimation of Sub-/Super-Synchronous Oscillation Based on Interpolated All-Phase Fast Fourier Transform with Optimized Window Function 基于优化窗函数的插值全相快速傅里叶变换的次/超同步振荡参数估计

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-29 DOI: 10.35833/MPCE.2023.000179

Bo Sun;Xi Wu;Xi Chen;Zixiao Zou;Qiang Li;Bixing Ren

{"title":"Parameter Estimation of Sub-/Super-Synchronous Oscillation Based on Interpolated All-Phase Fast Fourier Transform with Optimized Window Function","authors":"Bo Sun;Xi Wu;Xi Chen;Zixiao Zou;Qiang Li;Bixing Ren","doi":"10.35833/MPCE.2023.000179","DOIUrl":"10.35833/MPCE.2023.000179","url":null,"abstract":"In recent years, with increasing amounts of renewable energy sources connecting to power networks, sub-/super-synchronous oscillations (SSOs) have occurred more frequently. Due to the time-variant nature of SSO magnitudes and frequencies, as well as the mutual interferences among SSO modes with close frequencies, the accurate parameter estimation of SSO has become a particularly challenging topic. To solve this issue, this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher precision. First, by aiming at the sidelobe characteristics of the window function as evaluation criteria, a combined cosine function is optimized using a genetic algorithm (GA). Furthermore, the obtained window function is self-convolved to extend its excellent characteristics, which have better performance in reducing mutual interference from other SSO modes. Subsequently, a new form of interpolated all-phase fast Fourier transform (IpApFFT) using the optimized window function is proposed to estimate the parameters of SSO. This method allows for phase-unbiased estimation while maintaining algorithmic simplicity and expedience. The performance of the proposed method is demonstrated under various conditions, compared with other estimation methods. Simulation results validate the effectiveness and superiority of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10335162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141769488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linear OPF-Based Robust Dynamic Operating Envelopes with Uncertainties in Unbalanced Distribution Networks 基于线性 OPF 的不平衡配电网络不确定性稳健动态运行包络线

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-22 DOI: 10.35833/MPCE.2023.000653

Bin Liu;Julio H. Braslavsky;Nariman Mahdavi

引用次数: 0

Free Probability Theory Based Event Detection for Power Grids Using IoT-Enabled Measurements 利用物联网测量进行基于概率论的电网事件自由检测

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-22 DOI: 10.35833/MPCE.2023.000205

Hongxia Wang;Bo Wang;Jiaxin Zhang;Chengxi Liu;Hengrui Ma

{"title":"Free Probability Theory Based Event Detection for Power Grids Using IoT-Enabled Measurements","authors":"Hongxia Wang;Bo Wang;Jiaxin Zhang;Chengxi Liu;Hengrui Ma","doi":"10.35833/MPCE.2023.000205","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000205","url":null,"abstract":"Taking the advantage of Internet of Things (IoT) enabled measurements, this paper formulates the event detection problem as an information-plus-noise model, and detects events in power systems based on free probability theory (FPT). Using big data collected from phasor measurement units (PMUs), we construct the event detection matrix to reflect both spatial and temporal characteristics of power gird states. The event detection matrix is further described as an information matrix plus a noise matrix, and the essence of event detection is to extract event information from the event detection matrix. By associating the event detection problem with FPT, the empirical spectral distributions (ESDs) related moments of the sample covariance matrix of the information matrix is computed, to distinguish events from “noises”, including normal fluctuations, background noises, and measurement errors. Based on central limit theory (CLT), the alarm threshold is computed using measurements collected in normal states. Additionally, with the aid of sliding window, this paper builds an event detection architecture to reflect power grid state and detect events online. Case studies with simulated data from Anhui, China, and real PMU data from Guangdong, China, verify the effectiveness of the proposed method. Compared with other data-driven methods, the proposed method is more sensitive and has better adaptability to the normal fluctuations, background noises, and measurement errors in real PMU cases. In addition, it does not require large number of training samples as needed in the training-testing paradigm.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10327677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-Intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances 基于图形总变化的非侵入式住宅电器负载监控

IF 6.3 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-22 DOI: 10.35833/MPCE.2022.000581

Xiaoyang Ma;Diwen Zheng;Xiaoyong Deng;Ying Wang;Dawei Deng;Wei Li

{"title":"Non-Intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances","authors":"Xiaoyang Ma;Diwen Zheng;Xiaoyong Deng;Ying Wang;Dawei Deng;Wei Li","doi":"10.35833/MPCE.2022.000581","DOIUrl":"https://doi.org/10.35833/MPCE.2022.000581","url":null,"abstract":"Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power inlet. Despite several studies on the mining of unique load characteristics, few studies have extensively considered the high computational burden and sample training. Based on low-frequency sampling data, a non-intrusive load monitoring algorithm utilizing the graph total variation (GTV) is proposed in this study. The algorithm can effectively depict the load state without the need for prior training. First, the combined \u0000<tex>$K$</tex>\u0000-means clustering algorithm and graph signals are used to build concise and accurate graph structures as load models. The GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative algorithm. The introduction of the difference operator decreases the computing cost and addresses the inaccurate reconstruction of the graph signal. With low-frequency sampling data, the algorithm only requires a little prior data and no training, thereby reducing the computing cost. Experiments conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10327676","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Harmonic Virtual Impedance Control for Improving Voltage Quality of Microgrids 自适应谐波虚拟阻抗控制改善微电网电压质量

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2023-11-17 DOI: 10.35833/MPCE.2023.000447

Yang Wang;Xiang Zhou;Junmiao Tang;Xianyong Xiao;Shu Zhang;Jiandong Si

{"title":"Adaptive Harmonic Virtual Impedance Control for Improving Voltage Quality of Microgrids","authors":"Yang Wang;Xiang Zhou;Junmiao Tang;Xianyong Xiao;Shu Zhang;Jiandong Si","doi":"10.35833/MPCE.2023.000447","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000447","url":null,"abstract":"The effects of nonlinear loads on voltage quality represent an emerging concern for islanded microgrids. Existing research works have mainly focused on harmonic power sharing among multiple inverters, which ignores the diversity of different inverters to mitigate harmonics from nonlinear loads. As a result, the voltage quality of microgrids cannot be effectively improved. To address this issue, this study proposes an adaptive harmonic virtual impedance (HVI) control for improving voltage quality of microgrids. Based on the premise that no inverter is overloaded, the main objective of the proposed control is to maximize harmonic power absorption by shaping the lowest output impedances of inverters. To achieve this, the proposed control is utilized to adjust the HVI of each inverter based on its operation conditions. In addition, the evaluation based on Monte Carlo harmonic power flow is designed to assess the performance of the proposed control in practice. Finally, comparative studies and control-in-the-loop experiments are conducted.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10322690","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0