Exploring the Energy Benefits of Advanced Water Metering

Author(s): Berger, Michael A.; Hans, Liesel; Piscopo, Kate; Sohn, Michael D. | Abstract: Recent improvements to advanced water metering and communications technologies have the potential to improve the management of water resources and utility infrastructure, benefiting both utilities and ratepayers. The highly granular, near-real-time data and opportunity for automated control provided by these advanced systems may yield operational benefits similar to those afforded by similar technologies in the energy sector. While significant progress has been made in quantifying the water-related benefits of these technologies, the research on quantifying the energy benefits of improved water metering is underdeveloped. Some studies have quantified the embedded energy in water in California, however these findings are based on data more than a decade old, and unanimously assert that more research is needed to further explore how topography, climate, water source, and other factors impact their findings. In this report, we show how water-related advanced metering systems may present a broader and more significant set of energy-related benefits. We review the open literature of water-related advanced metering technologies and their applications, discuss common themes with a series of water and energy experts, and perform a preliminary scoping analysis of advanced water metering deployment and use in California. We find that the open literature provides very little discussion of the energy savings potential of advanced water metering, despite the substantial energy necessary for water’s extraction, conveyance, treatment, distribution, and eventual end use. We also find that water AMI has the potential to provide water-energy co-efficiencies through improved water systems management, with benefits including improved customer education, automated leak detection, water measurement and verification, optimized system operation, and inherent water and energy conservation. Our findings also suggest that the adoption of these technologies in the water sector has been slow, due to structural economic and regulatory barriers. In California, we see examples of deployed advanced metering systems with demonstrated embedded energy savings through water conservation and leak detection. We also see substantial untapped opportunity in the agricultural sector for enabling electric demand response for both traditional peak shaving and more complex flexible and ancillary services through improved water tracking and farm automation.

[1]  Ian F. C. Smith,et al.  Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks , 2013, Adv. Eng. Informatics.

[2]  Michael D. Sohn,et al.  Automated measurement and verification: Performance of public domain whole-building electric baseline models , 2015 .

[3]  Aimee McKane,et al.  Opportunities for Automated Demand Response in California Agricultural Irrigation , 2015 .

[4]  Cara Beal,et al.  Toward the digital water age: Survey and case studies of Australian water utility smart-metering programs , 2015 .

[5]  P. Mayer Residential End Uses of Water , 1999 .

[6]  Lj Grobler,et al.  Measurement and Verification of Energy Efficiency Savings in Industrial Facilities: The flaw of using energy intensities to determine savings , 2010 .

[7]  Nancy L. Barber,et al.  Estimated use of water in the United States in 2010 , 2014 .

[8]  C. Rocamora,et al.  Strategy for Efficient Energy Management to solve energy problems in modernized irrigation: analysis of the Spanish case , 2012, Irrigation Science.

[9]  Rodney Anthony Stewart,et al.  Web-based knowledge management system: linking smart metering to the future of urban water planning , 2010 .

[10]  Heng Huang,et al.  Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities , 2015, IEEE Transactions on Smart Grid.

[11]  Ariel Dinar,et al.  Irrigation water management policies: Allocation and pricing principles and implementation experience , 2004 .

[12]  Virginia Rapson,et al.  Impact of Demographic Change and Urban Consolidation on Domestic Water Use , 2005 .

[13]  Arlis Reynolds,et al.  The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures: January 2012 - September 2016 , 2018 .

[14]  Incorporating Energy Impacts into Water Supply and Wastewater Management , 2009 .

[15]  Bu-Sung Lee,et al.  Event Detection and Localization in Urban Water Distribution Network , 2014, IEEE Sensors Journal.

[16]  B. Kingdom,et al.  The challenge of reducing non-revenue water (NRW) in developing countries - how the private sector can help : a look at performance-based service contracting , 2006 .

[17]  Thomas M. Walski,et al.  A history of Water distribution , 2006 .

[18]  Gary Marks Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study , 2013 .

[19]  Dagnija Blumberga,et al.  Analysis of Factors Influencing Energy Efficiency in a Smart Metering Pilot , 2014 .

[20]  David Butler,et al.  Use of flow meters for managing water supply networks , 2004 .

[21]  José Maria Tarjuelo,et al.  Measurement and improvement of the energy efficiency at pumping stations , 2007 .

[22]  Nick R. Harris,et al.  How could sensor networks help with agricultural water management issues? Optimizing irrigation scheduling through networked soil-moisture sensors , 2015, 2015 IEEE Sensors Applications Symposium (SAS).

[23]  Koen Jacques Ferdinand Blanckaert,et al.  Water Saving and Energy Reduction through Pressure Management in Urban Water Distribution Networks , 2014, Water Resources Management.

[24]  Rodney Anthony Stewart,et al.  AGE OF INTELLIGENT METERING AND BIG DATA: HYDROINFORMATICS CHALLENGES AND OPPORTUNITIES , 2013 .

[25]  Daniel J. Howes,et al.  California Agricultural Water Electrical Energy Requirements , 2003 .

[26]  A. Horvath,et al.  Energy and air emission effects of water supply. , 2009, Environmental science & technology.

[27]  Ankit Jain,et al.  2015 California Demand Response Potential Study - Charting California’s Demand Response Future: Interim Report on Phase 1 Results , 2016 .

[28]  Sanem Sergici,et al.  The Impact of Informational Feedback on Energy Consumption -- A Survey of the Experimental Evidence , 2009 .

[29]  Kelly S. Fielding,et al.  An experimental test of voluntary strategies to promote urban water demand management. , 2013, Journal of environmental management.

[30]  Jessica Granderson,et al.  Energy Information Handbook: Applications for Energy-Efficient Building Operations , 2013 .

[31]  Nery Zapata,et al.  Water and energy management in an automated irrigation district , 2014 .

[32]  Christopher M. Bros,et al.  Energy and water quality management systems for water utility's operations: a review. , 2015, Journal of environmental management.

[33]  M. Sohn,et al.  Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection , 2014 .

[34]  Bryan W. Karney,et al.  A selective literature review of transient-based leak detection methods , 2009 .

[35]  Dan Koo,et al.  Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT) , 2015 .

[36]  H. Cooley,et al.  WATER-ENERGY SYNERGIES Coordinating Efficiency Programs in California , 2013 .

[37]  D. Sedlak,et al.  A changing framework for urban water systems. , 2013, Environmental science & technology.

[38]  Rodney Anthony Stewart,et al.  Smart metering: enabler for rapid and effective post meter leakage identification and water loss management , 2013 .