Building Central Plant System Performance Optimization through A Virtual Ambient Wet-bulb Temperature Sensor

Abstract

Ambient wet-bulb temperature measurement is critical in the water-cooled chiller plant system to enhance the holistic energy efficiency through advanced control strategies, such as the cooling tower temperature relief, condenser water supply temperature reset, and so on. The outside air (OA) wet-bulb temperature is usually measured either by a psychrometer or a combination of an OA relative humidity sensor and an OA dry-bulb sensor. However, these conventional measuring devices are notoriously costly and frequently problematic in consideration of the accuracy and reliability. This paper proposes a black-box-based virtual ambient wet-bulb sensor through adopting a low-cost but relatively accurate dry-bulb temperature sensor and the local weather data, either the typical meteorological year (TMY) weather data or the real-time weather data available online. Further, a dynamic real-time calibration algorithm was simultaneously developed to minimize the measurement error. A case study in a ten-story office building in Austin, Texas was implemented to demonstrate the feasibility of this strategy. It reveals that the virtual sensor combined with the uniquely developed control algorithm could greatly improve the readings of the ambient wet-bulb temperature, thus guarantee the in-field chiller plant performance optimization as expected by the proposed control strategies.