Optimize your consumption, production and batterystorage of electricity with dynamic prices
-
Updated
Nov 22, 2024 - Python
Optimize your consumption, production and batterystorage of electricity with dynamic prices
This repo features a deep reinforcement learning Home Energy Management System for cost-effective heating. It optimizes energy consumption using advanced algorithms, outperforming an optimal linear programming solution.
A modified uplift modeling technique to convert "treatment nonresponders" to "responders" is proposed through multifaceted interventions in market campaigns.
Includes multiple Scientific Computing & Algorithm Building Applications like Root Finding, Cost Minimization, Monte Carlo Approximation, Random Walk, Signal Strength Analysis, Class Architecture applications etc.
Monetary Worth Maximization, Cost Minimization and Network Flow cases; where LP approach is applied
Add a description, image, and links to the cost-minimization topic page so that developers can more easily learn about it.
To associate your repository with the cost-minimization topic, visit your repo's landing page and select "manage topics."