This project was awarded to demonstrate the ability to affect and optimize mercury speciation and multi-pollutant control using non-intrusive advanced sensor and optimization technologies. The intent was to demonstrate plant-wide optimization systems on a large coal fired steam electric power plant in order to minimize emissions, including mercury (Hg), while maximizing efficiency and maintaining saleable byproducts. Advanced solutions utilizing state-of-the-art sensors and neural network-based optimization and control technologies were proposed to maximize the removal of mercury vapor from the boiler flue gas thereby resulting in lower uncontrolled releases of mercury into the atmosphere. Budget Period 1 (Phase I) - Included the installation of sensors, software system design and establishment of the as-found baseline operating metrics for pre-project and post-project data comparison. Budget Period 2 (Phase II) - Software was installed, data communications links from the sensors were verified, and modifications required to integrate the software system to the DCS were performed. Budget Period 3 (Phase III) - Included the validation and demonstration of all control systems and software, and the comparison of the optimized test results with the targets established for the project site. This report represents the final technical report for the project, covering the entire award period and representing the final results compared to project goals. NeuCo shouldered 61% of the total project cost
while DOE shouldered the remaining 39%. The DOE requires repayment of its investment. This repayment will result from commercial sales of the products developed under the project. NRG's Limestone power plant (formerly owned by Texas Genco) contributed the host site, human resources, and engineering support to ensure the project's success.