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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This National Energy Technology Laboratory (NETL) analysis is a techno-economic evaluation of chemical precipitation followed by low hydraulic residence time biological treatment, which was identified as Best Available Technology for treatment and control of selenium emissions from wet flue gas desulfurization wastewater streams.
This U.S. Department of Energy/National Energy Technology Laboratory techno-economic analysis evaluates those parameters having the greatest performance and cost impact on wet flue gas desulfurization (FGD) effluent wastewater treatment systems, and air cooled condensers for dry cooling systems. Two supercritical pulverized coal power plants are considered: 1) an existing plant (modified for surface water discharge and air emissions consistent with limits for existing plants) retrofitted with wet FGD effluent wastewater treatment and 2) a greenfield plant constructed with an air-cooled condenser (ACC). Sensitivity analyses are completed on various process parameters associated with the wet FGD effluent wastewater treatment system and ACC to determine the impact on the net plant efficiency and levelized cost of electricity (LCOE). Research and development targets are recommended for the parameters shown to have the greatest potential impact on cost or performance.
Final presentation for a DOE/NETL journal manuscript that describes an analysis of treating emissions of bromides in flue gas desulfurization wastewater.
This presentation reviews the results of our research on flue gas desulfurization effluent treatment modeling and speciation analysis before and after physical/chemical biological treatment using aqueous chemistry software.<br>
A method of reducing sulfur concentration in fly ash, flue gas desulfurization (FGD) ash, and mixtures thereof by contacting the fly ash, FGD ash, or mixtures thereof with an aqueous acidic solution, for a time, at a temperature, and at a liquid-to-solid ratio wherein the sulfur concentration within the fly ash, FGD ash, or mixture thereof is reduced to no more than 5 wt % SO.sub.3 based on the total weight of dry fly ash, FGD ash, or mixture thereof so treated.
Flue gas desulfurization systems (FGD) mitigate air pollutants from coal fired power plants. However, such systems produce wastewater that contains other pollutants such as mercury, arsenic, nitrogen, and selenium that must be removed before the water is released back into the environment. Selenium is of interest because chronic low doses of selenium (ng/L) can cause detrimental ecological consequences. Biological treatment can be utilized to remove selenium from FGD wastewater, but the microorganisms involved in this process and environment within the FGD effluent have not been well studied. This study identifies the microorganisms in selenate-enriched and selenite-enriched FGD effluent that can reduce selenium oxyanions to elemental selenium. Knowing more about these organisms can lead to an eventual optimization in the biological removal of selenium species in these wastewaters.
Data from the US EPA FGD Database containing FGD effluent data from selected U.S. coal power plants. Original data from: Nguyen, Dan-Tam, Eastern Research Group. Sep 29, 2015. Analytical Database for the Steam Electric Rulemaking - DCN SE05359. https://www.regulations.gov/document/EPA-HQ-OW-2009-0819-5640
Case studies of selected streams from the EPA FGD Database. Includes OLI Studio and Geochemist's Workbench example files. Original data from: Nguyen, Dan-Tam, Eastern Research Group. Sep 29, 2015. Analytical Database for the Steam Electric Rulemaking - DCN SE05359. https://www.regulations.gov/document/EPA-HQ-OW-2009-0819-5640
This topical report summarizes results from developing a generic dynamic water balance tool which can be used by coal-fired power plant operators to evaluate FGD water management strategies. EPRI is using a statistical software model created on the GoldSim platform and data from coal-fired energy plants to determine the fraction of power plant water needs that can be satisfied by electrodialysis reversal treatment and, correspondingly, the discharge volume and/or byproducts that still need to be managed. The generic model is designed to accept a number of easily obtainable process variables and generate probabilities of resultant water characteristics. The model is also constructed as a universal process flow; one that can be adjusted to accommodate most major components of an FGD blowdown handling system. The generic model is dynamic and utilizes user-inputted operational variation in water quality and quantity to best provide a probabilistic representation of potential performance outcomes. In order to account for complexities of water composition and treatment, a separate chemical modeling software is used to evaluate water chemistry and unit operation performance. The thermodynamic modeling software, OLI Studio, is employed to convert ion data from laboratory analyses into balanced molecular concentrations that are classified as dissolved and suspended solids. The dynamic water model is designed to import a total of 11 species commonly found in FGD blowdown water as molecular concentrations.Water management unit operations are used in the model and categorized by either physical unit operation blocks or chemical unit operations blocks. As the name implies, the physical water treatment blocks are unit operations that are exclusively physical changes to the system (e.g., separations and volume changes). The chemical water treatment blocks are unit operations where chemical changes occur and require the use of OLI Studio to characterize subsequent streams. Water and material balances from three unique coal-fired power plants were obtained and preliminary modeling on the dynamic water balance tool was performed using the extracted data from these power plants. These three power plants were chosen due to their unique configurations and water profiles that represented a variety of operational changes. Results from using the dynamic tool with the three plant configurations are presented and discussed in the context of the existing tool and planned future capabilities.