Resumen
Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE) Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE) and ±5% for normalized mean bias error (NMBE). The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.