Electrification of oil refineries through multi-objective multi-period graph-theoretical planning: A crude distillation unit case study

Electrification using renewable energy sources is the key to paving a sustainable and cleaner future for the oil and gas sector, which is known to be a significant carbon dioxide emitter. Nevertheless, the suitability of the electrification designs heavily depends on the seasonal availability of renewable energy sources. This work proposes to use a multi-period graph-theoretical (P-graph) approach to determine the optimal retrofit strategy to achieve electrification with consideration of economic and environmental factors. Both single-period and multi-period models are considered via a graph-theoretical approach to rank and evaluate all the combinatorically feasible electrification pathways based on the overall performance. The effectiveness of the proposed method is developed using a crude distillation unit (CDU) case study adopted from a multinational company. The effectiveness of the proposed method is illustrated using a crude distillation unit (CDU) case study shown in three different scenarios that include prioritizing economic aspect (Scenario 1), prioritizing environmental aspect (Scenario 2), and considering equal importance of both aspects (Scenario 3). For single-period operation, the results showed a mix of natural gas and hydropower energy, exclusive use of onshore wind energy, and a mix of onshore wind energy and biogas cogeneration energy for Scenario 1, Scenario 2, and Scenario 3, respectively. In contrast, the multi-period model also utilized nuclear energy for Scenario 2 and Scenario 3 given the seasonal availability constraint. Following that, a sensitivity analysis is conducted to see the effect of the absence of the most influential energy sources on the optimal solution of each scenario and the top solutions under budget and CO2 emission constraints. Pareto analysis is outlined to offer an understanding of tradeoffs between differently prioritized solutions that decision-makers can select. The combination of the proposed analysis provides a systemic approach towards transforming traditional industries towards a cleaner future via electrification.