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2023
Conference Paper
Title
Multi-Criteria Scenario Development for Linear Optimization Models Utilizing Carbon-Containing Exhaust Gases
Abstract
Using the exhaust gases from the steel mill generation to produce chemicals can be a promising carbon capture and utilization (CCU) concept. Applying the model-based mathematical approach with mixed-integer linear programming (MILP) makes it possible to determine the optimal production pathway. However, the MILP aims the uncertain future to evaluate the long-term feasibility. It requires a hypothetical construction to show possible future states. This study aims to develop scenarios as input data for MILP models, representing a comprehensible future description. The investigation domains are determined as the technical, economical, and ecological perspectives to fulfil the multi-criteria evaluation. The factors from domains are projected qualitatively and quantitatively through objective estimations. The mutual relationships between the factors from the different domains such as the electricity price, Carbon footprint, and technical efficiency are implemented properly. The result is represented as five different scenarios: (1) Business as usual (BAU), (2) CO 2 reduction & RE share target (RE-Boom), (3) Technical improvement & Market booming (Market-Boom), (4) Energy & Market crisis (Crisis) and (5) Hydrogen booming (H 2-Boom). The scenarios depict the meaningfully different condition of the CCU concept with the most consistent and plausible combination of the key factors. Additional remarkable results from this study are the rough estimations of the initial capital and operating expenditures through the independently developed method. Consequently, the generated scenarios can be used for MILP models to promote the transparency and traceability of the further decision-making process.
Open Access
Rights
CC BY-SA 4.0: Creative Commons Attribution-ShareAlike
Language
English