A Web-Based Data Management and Analysis System for CO2 Capture Process

Abstract

Fossil fuels constitute a major energy resource for Canada. In 2002 alone, the production of oil, gas and coal contributed over $30 billion to the Canadian economy. Fossil fuel is presently the world’s most abundant, economical and reliable fuel for energy production. However, the industry now faces a major challenge because the production of fossil fuels including coal, crude oil and gas, and the processes currently used for energy production from such fuels, can have adverse environmental consequences. Hence, along with the positive economic advantages of energy production using fossil fuels come the responsibility of mitigating the consequent adverse environmental and climate-change impacts (Harrison et al., 2007). Carbon capture and storage (CCS) is an approach for reducing carbon dioxide (CO2) emissions to the environment by capturing and storing the CO2 gas instead of releasing it into the air. The application of CCS to a modern conventional power plant could reduce CO2 emissions to the atmosphere by approximately 80-90% compared to a plant without CCS (IPCC, Metz, & Intergovernmental Panel on Climate Change Working Group III, 2005). CO2 capture technologies mainly include: chemical absorption, physical absorption, membrane separation and cryogenic fractionation. Among these technologies, chemical absorption of CO2 is one of the most mature technologies because of its efficiency and low cost. The highly complex CO2 absorption process generates a vast amount of data, which need to be monitored. However, industry process control systems do not typically incorporate operators' heuristics in their intelligent control or data analysis functionalities. Our objective is to construct an intelligent data management and analysis system that incorporates such human experts' heuristics. The Data Analysis Decision Support System (DADSS) for CO2 capture process reported in (Wu & Chan, 2009) is a step towards filling this gap in automated control systems. However, the DADSS is a standalone PC-based system with limited flexibility and connectivity. In this paper we present a web-based CO2 data management and analysis system (CO2DMA), which overcomes these limitations. The system presented in this paper was built based on data acquired from the Pilot Plant CO2 capture process of the International Test Centre for CO2 capture (ITC), located at the University of Regina in Saskatchewan, Canada. The CO2 capture process at the ITC is monitored and controlled by the DeltaV system (Trademark of Emerson Process