Introduction:
Any urban city is a hub which has 80% of the total population living there due to better opportunities present there. City has many residential buildings, office buildings and other means of accommodation. Given the amount of people staying there, energy consumption is certainly high. There have been many studies done so far by urban scientists to understand energy consumption.In addition to this there is recently a new law passed for energy star score. This has caught my attention and hence, I would like to study the energy consumption for New York City for different types of buildings.
Data:
1. LL84 data:
‐ Property info (BBL, Address, Coordinates, Typology)
‐ Energy info (Total consumption, Energy use intensity, GHG emissions)
‐ Occupancy (Number of units, Operating hours, Worker density)
2. PLUTO:
-Building Info (Number of floors, number of buildings)
Method:
In order to understand factors responsible for energy consumption, I plan to use the following:
1. Linear Regression: To understand relationship between energy consumption and various other attributes (Number of floors,age of building, etc)
2. Multivariate regression: To get an equation for energy consumption based on the factors observed above.
Problem Statement: Understand energy consumption for multi family and office buildings and identify factors responsible for the same.
The reason to choose multi family and office buildings are the top two highest number of buildings occurring in the LL84 dataset. Therefore, there is enough data to perform analysis. Also these buildings have population in big numbers. Analyzing for these can help in understanding the overall energy consumption.
Expected Output: Factors contributing to energy consumption for multi family and office buildings.