Validation Framework for Model Predictive Control in Residential Buildings: An EnergyPlus-Python Co-Simulation Approach

Centeno Padilla M.; Snairder Jamir Chavez Ortiz A.; Mendoza Acosta A. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.1945

Resumen

Buildings account for a significant share of global energy consumption, motivating the development of advanced control strategies to improve energy efficiency while maintaining acceptable thermal comfort. Model Predictive Control (MPC) has shown strong potential for HVAC energy management; however, a persistent gap remains between theoretical developments and practical adoption due to the lack of structured validation procedures prior to real-world deployment. To address this challenge, this paper introduces a structured simulation-based validation framework for predictive energy control in residential buildings, designed to support pre-deployment decision-making. The framework integrates EnergyPlus with a Python-based MPC implementation through a co-simulation architecture, following the VDI 2206 systems engineering methodology to ensure traceability across requirements definition, system design, integration, and validation stages. The proposed approach is demonstrated through a case study of a residential building representative of tropical coastal conditions in Lima, Peru. An MPC-based HVAC control strategy is evaluated against a conventional proportional-integral (PI) controller under identical climatic and operational conditions. Performance is assessed using quantitative indicators, including total HVAC energy consumption, thermal comfort deviation, control stability, and computational response time. Simulation results show improved thermal stability, smoother control behavior, and a quantified reduction in energy consumption of 21% compared to the PI baseline, while maintaining acceptable comfort levels. The main contribution lies in a replicable engineering-oriented validation framework that supports systematic evaluation and reduces implementation risks in building energy management applications.

Instituciones: Universidad Tecnológica del Perú