Model Predictive Control for MicroCSP Integration into a Building HVAC System

Abstract

Micro-scale concentrated solar power (MicroCSP) is a promising technology that uses solar energy to provide electrical energy and thermal energy for use in buildings. This paper presents a model predictive control (MPC) framework to minimize the energy consumption of the building heating, ventilation, and air-conditioning (HVAC) system by integrating it with a microCSP. To this end, a microCSP model is developed and then integrated to the building model of an office building in Michigan Technological University. The designed MPC framework optimizes thermal energy storage (TES) usage and thermal energy flows from the heat pumps to the building rooms. The optimal control results show that the integration of microCSP to the building HVAC system reduces the HVAC energy consumption by almost half (4752%) by optimally utilizing the solar energy. The designed MPC framework provides 46% energy saving, compared to a heuristically designed rule-based controller for the combined HVAC and microCSP systems.