Electric power load dataset

Published: 17 February 2022| Version 1 | DOI: 10.17632/tj54nv46hj.1
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Description

Electric power load (active power load) data is created based on hourly voltage (V), current(I) and power factor(pf) information available at 33/11 KV substation (Godishala, huzurabad, Telangana state, India). Hourly voltage, current and power factor information collected during the period from 01.01.2021 to 31.12.2021. Based these values (V,I and pf) 3-phase load on the substation at each hour calculated. This data consists hourly load, status of the day [weekday:0 and weekend:1], season[Winter:1, Summer:2 and Rainy:0], hourly temperature and humidity information. While preparing the data total 66 missing values are found. This missing data is due to shutdown of the substation for maintenance or power outage. Missing values are replaced with average of load at previous day and next day but at same time of load data missing (In case of Tuesday, Wednesday, Thursday and Friday). Whereas in case of missing load data related to Monday then average of load at Saturday and Tuesday considered, Similarly if the missing load data belongs to Saturday then average of load at Friday and Monday is considered. If the missing load data belongs to weekend then average of load at previous weekend and next weekend considered. This dataset consists total 8760 hourly load data values. Load data available in this data set are in kilo-watts, temperature in degree Fahrenheit and humidity in percentage. It has been observed that load data distribution has a mean value of 2130kW, standard deviation of 1302kW, minimum load is 412kW and peak load is 6306kW. Total number of hours substation shutdown happened in the year 2021 is 66 hours. During the year 2021, godishala town feeder (F1) has 25 outage hours, Bommakal feeder (F2) has 71 outage hours, Godishala rural feeder (F3) has 97outage hours and Raikal feeder(F4) has 46 outage hours.

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Institutions

SR Engineering College

Categories

Machine Learning, Forecasting, Demand Forecasting, Energy Forecasting

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