Development and evaluation of optimization-based air economizer strategies

Abstract

This paper describes two new strategies for controlling air economizers. The model-based control strategy uses a model to estimate the load on the cooling coil for 100% outdoor air and minimum outdoor air and transitions dampers between these two positions to minimize the load. The optimization-based control strategy uses a cooling coil model and a one-dimensional optimization routine to determine the fraction of outdoor air that minimizes the coil load. A coil model based on the contact–mixture analogy was adopted for this study and validated with experimental data. Simulations were used to compare the new economizer control strategies with traditional strategies. Simulations evaluated the sensitivity of the annual and peak cooling loads to outdoor air and return air sensor errors and climatic conditions. Incorrect control decisions stemming from sensor errors reduce the achievable energy savings and lead to higher peak hourly loads. For a scenario representative of poorly maintained sensors, the lowest annual coil loads of the economizer strategies investigated are 3.0–40.3% higher than those achieved for the ideal scenario of optimization-based control and ideal sensors (i.e., no sensor errors), and the lowest peak hourly loads for those cases are 6.8–84.1% higher than those for the ideal scenario.