The open source repository for Electricity Maps data parsers that powers the world's most comprehensive electricity data platform

⚡ Energy consumption metrology agent. Let "scaph" dive and bring back the metrics that will help you make your systems and applications more sustainable !

Home Assistant integration for UK SMETS (Smart) meters pulling data from the DCC via the Hildebrand Glow API

Whole building non-residential hourly energy meter data from the Great Energy Predictor III competition

🌍 Tracarbon tracks your device's energy consumption and calculates your carbon emissions using your location.

View resource consumption trends, history, analysis, and insights.

Générateur de graphiques de consommation d'électricité Linky pour affichage sur Kindle

🐈 CATS: the Climate-Aware Task Scheduler 🌍

Import smart meter metrics from smarthub into VictoriaMetrics or InfluxDB

Software for monitoring the electricity consumption of a home with a Raspberry Pi

[KDD 2025] NILMFormer: A Sequence-To-Sequence Non-Stationarity Aware Transformer for Non-Intrusive Load Monitoring

IOT ANDROID BASED SMART HOME AUTOMATION SYSTEM USING FIREBASE , ARDUNIO, JAVA, NODE JS

A simple utility that you can use to access your Evergy account and retrieve you meter readings.

A simple node to connect to Enedis Linky smart-meter to fetch your datas

Over 10 years of hourly energy consumption data from PJM in Megawatts

[ACM e-Energy23] Appliance Detection Using Very Low Frequency Smart Meters Time Series

A Moroccan Buildings’ Electricity Consumption Dataset. MORED is made available by TICLab of the International University of Rabat (UIR), and the data collection was carried out as part of PVBuild research project, coordinated by Prof. Mounir Ghogho and funded by the United States Agency for International Development (USAID).

Unofficial API for 'elektrum.lv' for electric meters data fetching

[VLDB 2024] ADF & TransApp: A Transformer-Based Framework for Appliance Detection Using Smart Meter Consumption Series

Importa en el panel de energía el consumo y coste de electricidad desde ufd.es y ree.es. Calcula las facturas desde cnmc.gob.es.

Parses electric utility companies (Cez)

No description provided.

Home Assistant UTE (Administración Nacional de Usinas y Trasmisiones Eléctricas) component for Uruguay 🇺🇾

This project will present an applied and game-like approach to simulating the load growth, investment decisions by two types of generation technologies, demand-price responsiveness, and reliability, of a test-case power system. The simulation begins as a 9-bus system with existing generation (3 generators) and transmission lines (8 lines). System topology can be viewed in a figure throughout the game with the yearly generation and load at each bus. In addition, dynamic color-coding is used to highlight transmission lines that exceed MVA ratings and highlight bus voltages that violate any limits. The winning objective of the player company (you) is to maximize his profit. Reliability can be tracked by viewing the N-1 generator and line contingencies every year, but this does not influence profits. There are two generation technologies used: coal and gas turbine. Each technology will have a similar competitor in the simulation. The competitor can bring down the market price and reduce the player’s profits significantly. The clock starts at T=0 in the investment game with a historical record of past prices and projected prices based on lack of investment. As time moves forward in yearly increments, the load, prices, investment costs, and other variables are adjusted to that of the player’s performance. The player has the opportunity to study various profitable and unprofitable investment alternatives each year of the simulation. If he invests at the right location, and in the right planning year, his company can make windfall profits. Competitors randomly participate in adding extra generation in random areas of the system based on the competition level settings. The challenge for the user is to study the effects of his investment decisions on market prices, reliability, and his profitability.

UNOFFICIAL Red Eléctrica de España data client

No description provided.

No description provided.

IoT-based Smart Home Automation project to control 8 AC appliances and a smart door using ESP32 via Touch, Bluetooth, and Cloud with custom Android app.

A simple node to read data from Linky sent by an eeSmart D2L.

In this Project AVL trees are used to organize Electricty Records from Gaza by Date (Years, Months, Days)