A Data Driven Analysis on the Energy Performance and Efficiency of Water Treatment Plants

Water treatment plants are responsible for over 30 terawatt-hours per year of electricity consumption in the United States with an annual cost of nearly $2 billion [1]. Understanding the energy consumption in water treatment plants as well as the potential energy efficiency measures (EEMs) for these facilities can help the municipalities to prioritize the relevant energy efficiency projects based on their payback period and potential impact on their energy bill. In the present paper, the energy performance data for 192 water treatment plants is obtained from the U.S. Department of Energy Industrial Assessment Center (IAC) database. Energy audits were performed in these 192 sites between 2009 and 2022. The database includes the approximate location, square footage, annual energy use, annual plant production, identified EEMs, and their associated energy/cost savings as well as estimated payback period. The annual energy consumed per unit of production (EUP) and per unit of plant area (EUI) are calculated. The mean EUI and EUP for all the plants are found as 267.32 kBTU/ft2/Year and 265.97 kBTU/Thousand Gallons/Year, respectively. Also, the median EUI and EUP are evaluated as 42.4776 kBTU/ft2/Year and 8.203 kBTU/Thousand Gallons/Year, respectively. The analysis is also extended to understand the most promising EEMs for water treatment plants. An artificial neural network (ANN) is then developed to facilitate energy forecasting of water treatment plants using basic inputs including plant area and annual production. The outputs include estimated annual energy consumption and estimated potential savings that can be identified through conducting an energy audit. The training, testing and validation was satisfactory, but expected to much improve in the future with the addition of more assessment data to the IAC database. The ANN model will be the core of a basic energy analysis tool that can help the municipalities to easily evaluate the performance of their water treatment plants and estimate the potential savings that may be achieved as the result of performing an energy audit.