event 05 Jan 2017

Water-Energy Nexus // Characterizing cooling water source and usage patterns across US thermoelectric power plants: a comprehensive assessment of self-reported cooling water data

By Rebecca A. M. Peer and Kelly T. Sanders. Approximately 86% of US power production is generated in thermoelectric power plants that require water at sufficient quantities and temperatures for cooling. Water use for power generation is reported in terms of water withdrawals and water consumption, which are defined as the total volume of water removed from a source (river, reservoir, ocean, etc.) and the volumetric subset of withdrawn water that is not returned to the source (i.e. consumed via evaporative losses), respectively. Nationwide, almost half (45%) of annual US water withdrawals and about 3% of total US water consumption is dedicated to cooling thermoelectric power plants.

3303771747 a75b5c14c6 o power plant
(C) flickr / Wolfgang Staudt
The water requirements of power plants can vary significantly across different facilities and are influenced by characteristics such as cooling technology, fuel type, prime mover, pollution controls, and ambient climate. Cooling system configuration is the most significant characteristic governing a power plant's water use. Open-loop (or once-through) cooling systems withdraw large volumes of water, used once to condense steam exiting a steam turbine, while closed-loop (or recirculating) cooling systems withdraw smaller volumes per unit of generation by recirculating water continuously, at the expense of higher water consumption rates. Differences in the combustion (or conversion) characteristics of different primary energies (i.e. coal, natural gas, uranium, solar, etc.), as well as the prime mover technology used for conversion, also influence the efficiency, and thus the water requirements, of transforming primary energy into finished electricity. A facility using a steam turbine to convert primary energy into electricity, for example, typically has higher water requirements than a combined-cycle facility that combines a steam turbine with combustion turbines to increase the efficiency of electricity generation. Additionally, pollution controls for existing fossil-fueled generators typically require auxiliary systems that introduce parasitic power losses and additional water requirements for operation. Climatic variables such as air and water temperatures, streamflow, precipitation, and occurrence of extreme events can also impact the availability and/or required volumes of cooling water for power generation. While these general trends are understood, there exist only a few vetted datasets that detail the operational water requirements of US power plants. The lack of data availability surrounding water use at thermoelectric power plants was highlighted in 2009 by the Government Accountability Office. Macknick et al. compiled one of the first reviews of cooling water use rates (i.e. cooling water volume per electrical energy output) based on reported values from primary literature sources. This compilation of water use rates has been central to most recent studies evaluating cooling water use at the operational phase of power production. It characterizes power facility cooling water consumption and withdrawal rates based on fuel, cooling system, and prime mover configuration for a small sample of generators (on average four facilities per technology classification) reflecting the best available data at the time of publication [10]. Another recent report published by the US Geological Survey (USGS) estimated the water consumption and withdrawal rates for a large set of power plants based on heat budget models. While the USGS dataset represents a statistically significant sample size of power plants, water usage rates do not reflect the unique configurations of each individual power plant and are not reported by fuel or prime mover. Although self-reported cooling water data by power plant operators are collected and published annually from the Energy Information Administration (EIA), these data have been criticized for poor data quality and inconsistent reporting across US generation technologies. Furthermore, the data are difficult to use in practice as generation data are reported by unit specific prime mover, while water use data are collected and reported according to a cooling water system identification number. Since power plants often have multiple fuels, cooling systems, and/or prime movers, these data, although large in number, are not straightforward to analyze, and therefore, have not been used in many studies to date. Despite recent efforts by the EIA to improve data quality, no analysis has been completed to re-assess self-reported values since the 2008 data were analyzed by Averyt et al. Although there has been a growing body of analyses exploring the cooling water requirements of the power sector in the peer-reviewed literature across various energy futures, these studies lean almost exclusively on published water usage rates based on a small subset of power plants. Additionally, little analysis has been done to characterize emerging trends such as the expansion of dry-cooled and recirculating tower cooled power generation or the use of alternative sources of cooling water, such as reclaimed water from municipal and industrial wastewater treatment facilities. Given growing concerns regarding the water usage of power plants, an updated and expanded investigation is needed. The purpose of this study is to systematically analyze 2014 self-reported cooling water data published by the EIA in terms of plant-by-plant water usage rates, cooling water source type and quality, and geospatial trends in power plant cooling by watershed. The resulting vetted database of the cooling water characteristics of hundreds of power plant facilities is available in full in the SI document, offering the research community a statistically significant and geographically diverse database of plant-specific cooling water data for US power plants.


IOPScience website (open access)


December 2016


Environmental Research Letters, Vol. 11, No. 12

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