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california_renewable_energy_prod

Using L1 and L2 penalized regressions (LASSO and Ridge) to predict solar energy production by geolocation. Input data includes the historical weather forecast and various other features of atmospheric data such as radiance and humidity.

california_renewables

capstone_repo

Short-Term Solar Forecasting Using LSTMs

energyplus

EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.

hourly_energy_consumption_prediction

This repo contains files and jupyter notebooks for the project- Predicting energy consumption of the entire region in southern CA served by the SDGE (San Diego Gas and electric) utility based on the past 5 years of hourly energy consumption data.

solar

Insight Data Science Project: Predicting Photovoltaic Solar Panel Generation Using Machine Learning

solar-predictions

An analysis of solar installations

solarelectricanalysis

Solar_Electric_Programs_Reported_by_NYSERDA__Beginning_2000

time-series-analysis-and-weather-forecast-