frostdeer574/morocco-electricity-consumption-analysis

This project is dedicated to analyzing time-series data of electricity consumption in Morocco in three distinct zones. # morocco-electricity-consumption-analysis This project is dedicated to analyzing time-series data of electricity consumption in Morocco in 2017 in three distinct zones. The dataset used for this project is publicly available at Maven Analytics, and was originally downloaded from the UCI Machine Learning Repository. After cleaning and analyzing data with Python and SQL, here are the insights I've found: - Humidity has a reverse relationship with all other variables in the dataset, including power consumption in the three zones. - Temperature and windspeed positively correlate with power consumption, though the relationship with temperature is stronger, with an average of around 0.42 for three zones. - After the temperature reaches around 20 degrees Celcius, power consumption is more likely to rise sharply. - In all three zones, power consumption reaches its bottom between 5-7 AM and reaches its peak at 8 PM. - There are no significant fluctuations in power consumption on a weekly level. - On an annual level, however, multiple differences come to mind: - Electricity usage in Zone 1 slowly climbed until August, then fell to levels below January at the end of the year. - Zone 2 experienced a similar climb until August, but recovered and roze again after a fall in September. - Zone 3 had the least stable trajectory of all: its power consumption rose sharply until July, then rapidly fell to 11000 kW/h in December - the lowest average monthly rate of all three zones. Knowing these patterns, electricity providers can better adjust electricity consumption and supply to cut unnecessary costs and promote sustainable energy production.