Open AccessPrediction of Electricity usage in Industries by Big Data
Author(s) -
Chelikani Malyada*,
R. Keerthana,
P. V. V. Rama Rao,
R. Keerthana
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c8375.019320
Subject(s) - electricity , electric power industry , mains electricity , computer science , power (physics) , big data , voltage , service (business) , ac power , product (mathematics) , reliability engineering , electrical engineering , industrial engineering , data mining , engineering , business , marketing , mathematics , physics , geometry , quantum mechanics
Electrical industry is a main source industry in which where almost every other industry of many kinds are dependent on it. Not only the industries but also many Smart cities are connected with the different supply of current in which the current is used and to run the homes with the power supply. In the base paper we have taken the PMU data is collected which contain magnitude and phase angle components of the readings from PMU and the details of the fluctuations, deviations are only given so we have gone some extension to the paper and we have done the forecasting of the data by taking more of components like Logtime, current voltage (CV), active power (AP), reactive power (RP), apparent power, power factor, temperature, product weight and we are forecasting the data:To predict the energy usage.To provide monthly billing information and graphical report.To provide individual home appliance unit graphical report.Alert message service for the consumer.