ABSTRACT
This study investigated the greenhouse gas performance of an operating plant from a business intelligence perspective. 2017-2021 GHG data was collected from the plant, transformed, and loaded into Microsoft Power BI, which was used to build the data model. A dynamic visual dashboard was created for data analysis. The analysis was categorized into areas based on the requirements of the functional dashboard. These categories were GHG emissions per time period, top emitting process units, distribution of GHG emissions by pre-defined categories, and energy intensity. The dashboard showed stable emissions and energy intensity from 2018-2021. Dashboard analysis also demonstrated major emissions contributions from gas turbine generators and fired heaters, mainly from fuel I, highlighting key focus areas for future GHG reduction initiatives. GHG abatement strategies were proposed to provide direction for improvement. Although the dashboard was intended to aid strategic decision making, it can be adapted for greater insights and for operational and tactical decision making by using more data in the model and closer cooperation with data and process owners and operators.
