What price to pay? Auto-tuning a building MPC controller for optimal economic cost
Abstract
Demand-side management (DSM) programs introduce complex pricing, requiring advanced control for cost minimization. Model Predictive Control (MPC) offers a solution but its performance hinges on appropriate hyperparameter tuning. We propose using Constrained Bayesian Optimization (CONFIG) to automate this process. In a case study, our optimized MPC reduced electricity costs by 26.90% compared to a rule-based controller and by 17.46% versus an manually tuned MPC. Analysis of real contracts further showed that optimal DSM program selection can lower monthly bills by up to 20.18%, demonstrating a data-driven path to significant consumer savings.
Fields of Study & Subjects
Advanced Control Systems Optimization
Publication details
- Journal / source
- Control Engineering Practice
- Volume
- 174
- Pages
- 107023–107023
- Publication date
- 1 May 2026
- Language
- EN