2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)最新文献_第9页

Generation of Wind Energy with Kites: a Review of the Airborne Wind Energy Technology 利用风筝发电风能:机载风能技术综述

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326104

Laura Barros Cordeiro Peçanha, Natalia de Souza Barbosa Oliveira, Wagner Viana Bretas

引用次数: 0

Comparison Between Black Start and Islanding Process for The Establishment of a Rural Microgrid with Biogas Generator 沼气发电机组建设农村微电网黑启动与孤岛过程的比较

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326106

Patrícia Poloni, B. C. Pinheiro, Marcelo Henrique Manzke Brandt, Vanderlei Ferreira, Nádia Carolina Ribeiro, Natali Nunes dos Reis da Silva, Thiago José Lippo de França, Rogério Meneghetti, M. Vendrame

{"title":"Comparison Between Black Start and Islanding Process for The Establishment of a Rural Microgrid with Biogas Generator","authors":"Patrícia Poloni, B. C. Pinheiro, Marcelo Henrique Manzke Brandt, Vanderlei Ferreira, Nádia Carolina Ribeiro, Natali Nunes dos Reis da Silva, Thiago José Lippo de França, Rogério Meneghetti, M. Vendrame","doi":"10.1109/TDLA47668.2020.9326106","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326106","url":null,"abstract":"Microgrid arrangements have been applied in scenarios where is necessary to offer most reliability in the electricity supply system, requiring definitions of priority loads, transition between modes of operation, among others. This paper presents an analysis of two scenarios for establishing of a microgrid operating in the rural area in the south region of Brazil with a biogas generator. In the fist scenario the islanded mode is performed by Black Start procedure while in the second intentional inslanding is performed without interruption of energy supply. This paper present the modeling of the system in the Matlab/Simulink software using real data from the implanted microgrid and the results of the simulations and the analysis of the effects of the establishment of the microgrid island from the different strategies adopted. It is confirmed the islanding allows the continuous operation of loads and the generation of microgrid without the need to interrupt the power supply as occurs in Black Start.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130616504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Propagation of Supraharmonics Generated by PMSG Wind Power Plants into Transmission Systems PMSG风力发电厂产生的超谐波在输电系统中的传播

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326138

Benhur Zolett, R. Leborgne

{"title":"Propagation of Supraharmonics Generated by PMSG Wind Power Plants into Transmission Systems","authors":"Benhur Zolett, R. Leborgne","doi":"10.1109/TDLA47668.2020.9326138","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326138","url":null,"abstract":"This paper is focused on the propagation of supraharmonics into power transmission grids introduced by wind power plants (WPP) based on permanent magnet synchronous generator (PMSG) wind turbines. The methodology is based in steady state and time domain simulations performed by MATLAB Simulink®. As results steady state power flow and time domain voltages and currents are obtained and supraharmonic indicators are proposed for analysis. In order to simulate the electrical power system, transmission lines are modelled by Pi equivalent circuit based on distributed parameters and linear models of transformers are considered. Furthermore, wind power plants are modelled as aggregations of several wind turbines. A study case based on the west side of the Brazilian state of Rio Grande do Sul is proposed to validate the modelling and simulation methodology. Results show that the level of supraharmonics emission from WPP is straightly related to the PWM modulation of power inverters. Furthermore, the propagation of supraharmonics into transmission grids follows a linear tendency of decreasing according to the distance in transmission lines to the point of common coupling (PCC) of the wind power plants. Anyway, intrinsic characteristics at each point of the grid such as load profile, generation and presence of capacitor banks also influence the behavior of supraharmonic propagation.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114571720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Short-term electric load forecasting using neural networks: A comparative study 基于神经网络的短期电力负荷预测的比较研究

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326196

L. G. Rocha, Symone Gomes Soares Alcalá, L. P. Garcés Negrete

{"title":"Short-term electric load forecasting using neural networks: A comparative study","authors":"L. G. Rocha, Symone Gomes Soares Alcalá, L. P. Garcés Negrete","doi":"10.1109/TDLA47668.2020.9326196","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326196","url":null,"abstract":"Forecasting the short-term electrical demands of a distribution system is essential for efficient electric system planning and operation. A balance between generation and demand is the main requirement for efficient operation by the electric utilities. Therefore, a load forecast as accurately as possible is important to offer a good service with adequate economic viability. In this work, four types of short-term load forecasting based on neural networks are proposed and compared. A Nonlinear autoregressive neural network (NAR), a Nonlinear autoregressive neural network with external input (NARX), a Feedforward neural network (Feedforward), and a Time delay neural network (Timedelay) are modeled and simulated. A comparison among proposed neural networks is done using metrics established in the evaluation of neural networks, such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Correlation Coefficient (R). The data used in this work was extracted from the Operating Center of a local company of distribution of electric energy. These data are pretreated using curve smoothing techniques, and then, they are used to train the selected neural networks. Moreover, a simulation using the Prophet, a Facebook® procedure to predict time series, was made to compare the results with the mentioned neural networks.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114604002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Impacts of Photovoltaic Systems in Distribution Networks Using Droop Control 采用下垂控制的光伏系统对配电网的影响

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326225

D. Lima, Lucas F. de Souza, J. Vieira

引用次数: 1

Stochastic Assessment and Risk Management of Transient Stability based on PowerFactory and Python Interface 基于PowerFactory和Python接口的暂态稳定随机评估与风险管理

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326234

M. S. Chamba, Walter Vargas, Jaime Cristobal Cepeda

{"title":"Stochastic Assessment and Risk Management of Transient Stability based on PowerFactory and Python Interface","authors":"M. S. Chamba, Walter Vargas, Jaime Cristobal Cepeda","doi":"10.1109/TDLA47668.2020.9326234","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326234","url":null,"abstract":"This paper presents a novel simulation tool that exploits the feasibility of communicating DIgSILENT PowerFactory and Python to evaluate the impact of the electrical demand uncertainty regarding power system transient stability, considering the probabilistic analysis of the Critical Clearing Time (CCT). The probabilistic analysis of transient stability allows establishing a probability density function (PDF) of the CCT behavior. This PDF is calculated by means of Monte Carlo simulations in which the CCT is evaluated for each generated scenario. The bisection method is applied for calculating the CCT. This method consists in iteratively modifying the fault duration time (tf) and evaluating transient stability for each tf via the hybrid method SIME (Single Machine Equivalent). Finally, a proposal for assessing the risk involved in the transient stability assessment is structured using the concepts of Value at Risk (VaR) and Conditional Value at Risk (CVaR). The proposed methodology is tested in the 39-bus IEEE New England test system.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129675517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Linear Fresnel Concentrator: A Review of its Implementation in South American Countries 线性菲涅耳聚光器:在南美国家实施的回顾

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326201

S. Gulino, J. Rodas, R. Gregor

引用次数: 0

Real-time Health Condition Monitoring of SCADA Infrastructure of Power Transmission Systems Control Centers 输电系统控制中心SCADA基础设施健康状态实时监测

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326135

Jaime D. Pinzón, T. Osorno, J. Mola, Alexandra Valencia

{"title":"Real-time Health Condition Monitoring of SCADA Infrastructure of Power Transmission Systems Control Centers","authors":"Jaime D. Pinzón, T. Osorno, J. Mola, Alexandra Valencia","doi":"10.1109/TDLA47668.2020.9326135","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326135","url":null,"abstract":"The infrastructure for the supervision, control and data acquisition (SCADA) is critical for the operation of the electrical transmission network due to the complexity of the modern electrical power systems which are made of a big number of components and technical constraints for its operation. One failure in one of the many devices that are part of the SCADA could produce a failure in the supervision and control of one substation, one region or even a whole country; and because the hardware infrastructure needed to implement a SCADA system might come to be massive in terms of the numbers of devices for the communication network, servers and more; it becomes crucial to have a well-structured and efficient monitoring system for the SCADA infrastructure of any power transmission control center. In this paper it is proposed a monitoring scheme based on the Simple Network Management Protocol (SNMP) used to get realtime data of the devices involved in these systems, such as: servers, communication switches, workstations, routers and firewalls; and also, the real-time monitoring of essential software functions, not only from the SCADA but from the Energy Management System (EMS) as well. The acquired data is processed into early warning signs (alarms), tendency graphs and visualizations with real-time data that allows the administrators to manage the SCADA infrastructure in a preventive and not in a reactive manner, which secures the operation against failures and events. This scheme was implemented in four electrical power transmission control centers in South America which operate up to 500 kV grids. The implementation showed clear benefits in the use of this novel scheme because the detection, diagnostics and solution for possible risks in the system could be managed in an earlier stage than it used to be, which incremented the availability and reliability of the SCADA system infrastructure.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115055620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Forecasting hourly electricity demand of Uruguay for the next day using artificial neural networks 利用人工神经网络预测乌拉圭第二天的小时电力需求

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/TDLA47668.2020.9326206

Rodrigo Porteiro, Sergio Nesmachnow

{"title":"Forecasting hourly electricity demand of Uruguay for the next day using artificial neural networks","authors":"Rodrigo Porteiro, Sergio Nesmachnow","doi":"10.1109/TDLA47668.2020.9326206","DOIUrl":"https://doi.org/10.1109/TDLA47668.2020.9326206","url":null,"abstract":"This article presents different models applying computational intelligence to forecast the total hourly electricity demand of Uruguay for the next day. Short term electricity demand forecasting is crucial to optimize the economic dispatch of electricity generation, improving the rational use of resources. It also allows improving energy efficiency and demand response policies related with smart grids. Classical statistical models have been applied to predict electricity demand but with the recent development of computational hardware and the vast amount of data available from various sources, computational intelligence models have emerged as successful methods for prediction. In this article, two artificial neural network architectures are presented and applied to forecast the total electricity demand of Uruguay for the next day. The first architecture combines Long Short Term Memory units (LSTM) with fully connected neural networks layers, and the second architecture improves the first by adding a Convolutional Neural Network as first layer (CNN+LSTM). Both architectures use a dropout technique to avoid overfitting. An ExtraTreesRegressor model is used as benchmark to evaluate both architectures. Three steps of data preprocessing are carried out, including treating missing values, removing outliers, and standardization. Considering the high computing demands of the applied techniques, they are developed and executed on the high performance computing platform provided by National Supercomputing Center (Cluster-UY), Uruguay. Standard performance metrics are applied to evaluate the proposed models. The experimental evaluation reports successful forecasting results: the CNN+LSTM model has a mean absolute percentage error of 4.3% when applied to the prediction of unseen data.","PeriodicalId":448644,"journal":{"name":"2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125838841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

T&D LA 2020 Program

2020 IEEE PES Transmission & Distribution Conference and Exhibition - Latin America (T&D LA) Pub Date : 2020-09-28 DOI: 10.1109/tdla47668.2020.9326140

引用次数: 0