Session: 08-08-05 Renewable Energy V and Sustainable and Grid-Interactive Buildings

Paper Number: 69679

Start Time: Friday, 02:05 PM

69679 - Validation Approach for Energy Optimization Models of Grid-Interactive Buildings Using Co-Simulation 

The consumption and production of energy are more dynamic as distributed energy resources (DER) such as solar photovoltaic (PV) are deployed within the electric distribution system. The traditional energy price at a predetermined rate cannot accommodate these dynamics and can lead to wasted energy and higher costs for both utility companies and consumers. Commercial building and residential energy management systems are usually on a fixed schedule and are not able to respond to changes in energy price instantaneously. There is a need for a real-time pricing structure that can accommodate the fluctuating cost of energy based on supply and demand, and a need for an energy management system that is able to respond to the dynamic utility rate. As such, there is a need for a robust energy management control strategy and methodology to validate new approaches. Moreover, residential energy system control strategies have not received significant attention due to the low economic viability to individual end users in spite of their large impact at a scale. To address this gap, a strategy to control HVAC systems in a residential house was developed along with a validation methodology. A model of predictive control was implemented to optimize the thermostat setpoints and minimize energy cost for an individual residential house while maintaining thermal comfort of users. Using the dynamic pricing, current indoor temperature, and predicted outdoor temperature and solar radiation, the control algorithm optimizes the energy consumption by adjusting the temperature setpoint on an hourly basis. This model was integrated with EnergyPlus simulation via an open source co-simulation platform previously developed by the team. Total energy consumption and cost for consumers were compared between cases with the proposed model and with two baseline cases that use fixed-temperature setpoint control and adaptive setpoint control. The simple dynamic pricing model used in simulations was proportional to the demand of energy at that time of day. Thermal comfort of an occupant was evaluated by the amount of time that the temperature is outside of the comfort zone using an adaptive comfort model. This work will contribute to the development of utility dynamic pricing models and residential control strategies for grid-interactive buildings and homes. The simulation strategy enables the utility pricing models and control strategies to be tested independently so that a wide range of options can be considered. The outcome of this research can be expanded to different building models or locations in future work.

Presenting Author: Patrick McCurdy Santa Clara University

Authors:

Patrick J. McCurdy Santa Clara University
Kaleb Pattawi Mechanical Engineering Department, Santa Clara University
Chenli Wang National Institute of Standards and Technology
Thomas Roth National Institute of Standards and Technology
Coung Nguyen National Institute of Standards and Technology
Yuhong Liu Santa Clara University
Hohyun Lee Santa Clara University