A mathematical optimization technique for managing selective catalytic reduction for coal-fired power plants

Abstract

Selective catalytic reduction (SCR) is an emissions control technique that primarily reduces harmful emissions of oxides of nitrogen (NOx). To maintain SCR performance, catalyst layers maybe added, removed, or replaced to improve NOx reduction efficiency. To make these changes, power plants must be temporarily shut down, and SCR maintenance during scheduled power plant outages can be very expensive. Consequently, developing a fleet-wide SCR management plans that are both efficient at reducing NOx and limiting operating costs would be extremely desirable. We propose an SCR management framework that finds an optimal SCR management plan that minimizes NOx emissions using integer programming. The SCR management tool consists of two main modules—the SCR schedule generation module and the SCR optimization module. Furthermore, the SCR management framework addresses decision making from the fleet-wide perspective as well as a single plant as opposed to only a single plant, which is currently commercially available. We demonstrate the effectiveness of the tool and provide a tradeoff between NOx reduction and operating cost using Pareto optimal efficient frontiers.