Analyzed Google Satellite images to generate a report on individual house rooftop's solar power potential
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Updated
May 1, 2023 - Python
Analyzed Google Satellite images to generate a report on individual house rooftop's solar power potential
Enphase-API is an unofficial project providing an API wrapper (including local/LAN Gateway API) and the documentation for Enphase®'s products and services.
Dockerized Repo for "3D-PV-Locator: Large-scale detection of rooftop-mounted photovoltaic systems in 3D" based on Applied Energy publication.
Personal project, Low-level Visible Light communication system.
PyTorch models and pipeline developed for "DeepSolar for Germany". For reference, the paper can found at https://ieeexplore.ieee.org/document/9203258
Shows solar panel production, household consumption, and net household consumption.
Unofficial home assistant integration for Aton Green Storage photovoltaic system
Home Assistant Open-Meteo Advanced Solar Forecast Integration
Tool to Maximize the Return of the Solar Panel Investment
Predicting Rooftop solar energy potential using real-time solar irradiance data with auto extracted building footprints. Adjusting PV output in accordance to partial shading originating from surrounding obstacles such as trees, buildings, etc.
Tesla-API is an unofficial project providing an API wrapper to the local/LAN Tesla® Gateway API used by the Tesla® Powerwall
Unofficial python client for the Growatt API ⚡
Python scripts to export data from your Enphase Envoy system, can also upload to AWS
This project focuses on increasing renewable energy access in India using AI. ✨👌
Record and plot total power and string power from Fronius inverters
SPECTRA: Solar Panel Evaluation through Computer Vision and Advanced Techniques for Reliable Analysis
Python client library for eCactus ECOS API
Intelligent Deep Learning system for automated defect detection and classification on solar panels using YOLOv8 and TensorFlow.
🌥 Calculates the optimum solar panel tilt using cloud data
Code for my Bachelor's thesis "Drone image and video encoding and processing using machine learning"
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