Modeling and Optimal Control of Micro-CSP and a Building HVAC System to Minimize Electricity Cost

Abstract

This paper presents a model predictive control (MPC) framework to minimize the energy cost associated with the building heating, ventilation, and air-conditioning (HVAC) system integrated with a micro-scale concentrated solar power (MicroCSP) system. To this end, a MicroCSP model is developed and then integrated to the building model of an office building in Michigan Technological University. Then, an MPC framework is designed to optimize MicroCSP electrical and thermal energy flows for HVAC use in the building. The optimal control results show that the designed MPC framework reduces the HVAC energy cost by 37–42% for a sample sunny day by optimally utilizing the solar energy, compared to the HVAC system without MicroCSP with an MPC controller. The cost saving varies from 12% to 47% depending on seasonal weather variations.