High-Level Project Summary
Zeastellar is developed to find the current profitability of the user's location. The Zeastellar finds whether the solar energy is suitable for that particular location or not. With its advanced ML model Zeastellar finds the cost of installation and profitability of the installation(Here profitability means Total cost of the electricity / cost of Solar UNit x 100). We have collected various data to evaluate the profitability. The data includes Total area of Installation, Solar Irradiation, Performance Ratio and ENergy Yield of the unit. With this Datas and some more algorithm, Zeastellar postulates an accuracy of 65%.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
The electricity price in each country is observed and fed into the algorithm. ANd the live data of the radiation is dropped down from the North-west space agency and NASA. Usage(in KW ) * 12 * lifespan * cost / 100 -> this will give you the rough estimation of the current bill. With Dataset from the NREL Solar Radiation Research Laboratary [BMS], the pyreheliometer live data is being derived and fed into the algorithm.
Space Agency Data
The space agency data such as NREL Solar Radiation Research Laboratary [BMS] of pyrehelimeter and Nasa's advanced Power tool is fed into the algroithm.
Hackathon Journey
We have learnt about the Neural Net, Flask , Html, Css. Literally we had clustering issue while building the ML Model. It was a great experience.
References
Electricity Data
https://s3.amazonaws.com/datascope-ast-datasets-nov29/datasets/435/data.csv
Global Radiation
https://midcdmz.nrel.gov/apps/plot.pl?site=BMS;start=20200101;live=1;zenloc=222;amsloc=224;time=1;inst=60;inst=64;inst=65;inst=66;type=data;preset=0;first=3;math=0;second=-1;value=0.0;global=-1;direct=-1;diffuse=-1;user=0;axis=1;endyear=2021;endmonth=10;endday=1
Cell Dataset
https://www.sciencedirect.com/science/article/pii/S2352340917301476
Nasa Power Project:
https://power.larc.nasa.gov/
Tags
#Solar #Solar Energy #Solar_profitability #solar_unit
Global Judging
This project has been submitted for consideration during the Judging process.