A heat and mass transfer model of evaporation from the fur of a cow was coupled to a metabolic model of the animal to estimate the frequency of water spray and fan speed given input on environmental conditions. The model has been used to develop a controller that can vary the fan speed and spray frequency to maintain the animal core temperature at a target value. The controller was implemented on a platform provided by a commercial partner, and its performance is being compared against baseline control strategies used in a dairy in the Central Valley.
The project’s innovation includes improving controls for existing spray cooling systems by integrating an optimization algorithm based on a heat and mass transfer model of a dairy cow into the control system. The controller will operate the existing water spray solenoid valve at the desired frequency. The optimization algorithm developed through this project will be deployed using a commercially available control platform.
The project will reduce annual electricity consumption therefore improve electricity reliability. This reduction in electricity consumed by dairies will decrease stress on the electricity grid by reducing the total lad and lower electricity costs for dairy farmers. The project is consistent with the California Energy Commission's mission of leading the state to a 100 percent clean energy future. This project is expected to save 26 kWh per cow per year.
The project will reduce annual electricity consumption and lower electricity costs for dairy farmers.
The project is consistent with the state's goal of increasing energy efficiency and leading the state to a 100 percent clean energy future. This project is expected to save 26 kWh per cow per year in CZ 12 and 50 kWh per cow per year in CZ 13.
The project will reduce annual electricity consumption and potentially reduce stress on the electricity grid by reducing total load.
RMS Energy Consulting, LLC
Western Cooling Efficiency Center - UC Davis