# An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings

## TL;DR

This paper presents a specialized Model Predictive Control strategy for cost-effective operation of large-scale smart buildings, integrating HVAC, energy storage, photovoltaic generation, and demand-response participation.

## Contribution

It introduces a computationally efficient MPC approach for managing HVAC and storage in large-scale buildings considering multiple energy sources and demand-response constraints.

## Key findings

- The proposed MPC achieves cost savings in building operation.
- The approach remains computationally feasible for large-scale systems.
- Performance is validated under uncertainties and disturbances.

## Abstract

This paper deals with the problem of cost-optimal operation of smart buildings that integrate a centralized HVAC system, photovoltaic generation and both thermal and electrical storage devices. Building participation in a Demand-Response program is also considered. The proposed solution is based on a specialized Model Predictive Control strategy to optimally manage the HVAC system and the storage devices under thermal comfort and technological constraints. The related optimization problems turn out to be computationally appealing, even for large-scale problem instances. Performance evaluation, also in the presence of uncertainties and disturbances, is carried out using a realistic simulation framework.