390757 Multi-Objective Modeling, Simulation, and Optimization for Economically and Environmentally Conscious Decision Makings

Sunday, November 16, 2014
Galleria Exhibit Hall (Hilton Atlanta)
Tianxing Cai and Qiang Xu, Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX

Chemical facilities, where large amounts of chemicals and fuels are processed, manufactured, and housed, are at high risk to originate air emission events, including intensive flaring and toxic gas release caused by various uncertainties such as equipment failure, false operation, natural disaster, or terrorist attack. Chemical plant concentrated regions may suffer localized and transient air pollution events that violate national ambient air quality standards (NAAQS). Flaring emissions, especially intensive start-up flaring emissions from chemical plants, have potentially significant impacts on local air quality.Furthermore, geographic allocation of chemical plants significantly affects industrial business sustainability as well as regional environmental sustainability. According to site selection rules, the air quality impact to surrounding communities of a newly constructed chemical plant must be taken into account.  Therefore, it is very important to apply modeling, simulation, and optimization to provide economically and environmentally conscious decision makings and valuable quantitative engineering supports for multiple stake holders, including government environmental agency, regional chemical plants, and local communities.

In this paper, the general introduction will be given for our previously developed multi-systematic mathematical simulation and optimization models based on the methodology of multi-objective optimization. The first model will conduct the multi-plant start-up emission evaluation and help to provide control strategy. For any air quality violation is predicted to an AQCR, a multi-objective scheduling problem will be generated and solved to optimize the start-up sequence and start-up beginning time for all chemical plants. The scheduling model minimizes the overall air quality impacts to all of the AQCRs as well as minimize the total start-up time mismatch of all plants, subject to the principles of atmospheric pollutant dispersion.  The second model aims to detect the possible emission sources (chemical plants) and identify the abnormal emission profile (emission source location, starting time, time duration, dynamic emission rate and total emission amount) from an accidental emission source responsible for an observed emission event based on an available air-quality-monitoring network so as to support diagnostic and prognostic decisions in a timely and effective manner.It provides valuable information for investigations of accidents and root-cause analysis for emission events; meanwhile, it helps evaluate the regional air-quality impact caused by such emission events as well. The third model evaluates the potential air-quality impacts from candidate sites of a new chemical plant in order to optimize the final site determination by minimizing its air-quality impacts.  This study can not only determine the potential air-quality impact for allocation of multiple chemical plants with respect to regional statistical meteorological conditions, but also identify an optimal site for each new chemical plant with the minimal environment impact to surrounding communities.  Case studies are employed to demonstrate the efficacy of the developed methodologies.

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