Optimize your consumption, production and batterystorage of electricity with dynamic prices
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Updated
Nov 8, 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
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