Comtrade DELIVERS a solution for forecasting electricity demand

Our client, a world-leading grid energy storage company, needed a solution to reduce energy costs by predicting a moment to buy electricity when it’s more cost-effective and enable usage during more expensive peak hours.

A Case Study at a Glance

Challenges

  • Fluctuations in electricity demand and supply
  • Daily Peak prediction
  • Integration of large machine

Results

  • Reducing electricity cost for the end users
  • Improving client’s profit margin
  • A better utilization of renewable energy sources

Technology

  • Python with different frameworks (Django, Falcon, Flask, etc.)
  • Java for High-performance Microservices
  • React, Nodejs, Redux, Angular