A power quality prediction system

نویسندگان

  • Steven R. Shaw
  • Christopher R. Laughman
  • Steven B. Leeb
  • Robert F. Lepard
چکیده

This paper describes two hardware prototypes and estimation schemes for determining the parameters of a simple, physically based, point-of-use electric utility model using transient measurements. Parameters of the utility model are estimated using data collected by the prototypes. Frequency-dependent effects observed in previous work in this area are modeled. Performance of the techniques given is demonstrated by comparison of measured and predicted line voltage distortion during current transients created by several loads.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Online Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines

In this paper, a novel method is proposed to monitor the power system voltage stability using Support Vector Machine (SVM) by implementing real-time data received from the Wide Area Measurement System (WAMS). In this study, the effects of the protection schemes on the voltage magnitude of the buses are considered while they have not been investigated in previous researches. Considering overcurr...

متن کامل

Adaptive Network-based Fuzzy Inference System-Genetic Algorithm Models for Prediction Groundwater Quality Indices: a GIS-based Analysis

The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...

متن کامل

Coastal Water Level Prediction Model Using Adaptive Neuro-fuzzy Inference System

This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...

متن کامل

Enhancement of Power Quality in Grid Integrated System using DC-link Voltage PI Controlled VSC based Statcom

This paper demonstrates an enhancement of power quality in grid integrated systems with the help of the proposed control strategy for voltage source converter based active power filters. The Shunt Active Power filters (SAPF) are extensively utilized in modern grid integrated systems to diminish the power quality concerns associated with it. The SAPF is one of the various power filters, which ha...

متن کامل

Prediction of the Carbon nanotube quality using adaptive neuro–fuzzy inference system

Multi-walled carbon nanotubes (CNTs) are synthesized with the assistance of water vapor in a horizontal reactor using methane over Co-Mo/MgO catalyst through chemical vapor deposition method. The application of Adaptive Neuro-Fuzzy Inference System (ANFIS) technique for modeling the effect of important parameters (i.e. temperature, reaction time and amount of H2O vapor) on the qualit...

متن کامل

A novel method based on a combination of deep learning algorithm and fuzzy intelligent functions in order to classification of power quality disturbances in power systems

Automatic classification of power quality disturbances is the foundation to deal with power quality problem. From the traditional point of view, the identification process of power quality disturbances should be divided into three independent stages: signal analysis, feature selection and classification. However, there are some inherent defects in signal analysis and the procedure of manual fe...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • IEEE Trans. Industrial Electronics

دوره 47  شماره 

صفحات  -

تاریخ انتشار 2000