Defining Influent Scenarios: Application of Cluster Analysis to a Water Reclamation Plant

Abstract

AbstractProcess control at older water reclamation plants (WRPs) can be challenging as operators work to balance higher energy costs and more stringent effluent limitations while managing fluctuating loads. To better understand WRP loading characteristics, we developed a classification system for the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) Calumet WRP by combining k-means cluster analysis with cross-tabulation analysis. Based on weather and influent composition characteristics, we identified 25 clusters; nine of those clusters are significant (99% confidence level) based on chi-square tests. Dry weather and middle temperature conditions after wet-weather days are common, and compared to cold-weather flows, warm-weather flows are more likely to have large precipitation events and more variation in influent quality. To explore how information about influent scenarios could inform process control and improve process efficiency, we also developed a process simulation model. The mod...