Scenario-based assessment for optimal planning of multi-carrier hub-energy system under dual uncertainties and various scheduling by considering CCUS technology

This paper provides a scenario-based assessment strategy for the optimal scheduling of a hub by considering uncertain parameters (electricity price and wind turbine output power) and carbon capture utilization and storage (CCUS) technology simultaneously. CCUS technology helps overcome pollution issues, on the one hand, and earn revenue for the power system, on the other hand. Three different planning horizons which include deterministic, stochastic, and robust models are investigated and compared. Energy hub (EH) aims to minimize the total cost and environmental pollution simultaneously while considering the effect of objective function priority. The problem is then modeled as real mixed integer programming (RMIP) and is solved in GAMS software by using CPLEX; the results are compared with other solvers. Epsilon constrains (EPC) method and fuzzy satisfying approach are used to select the optimal solution based on the presented model. In the end, a sensitivity analysis is performed. Results show that by utilizing CCUS technology, the cost and pollution for all the planning horizons are reduced properly. CCUS's profits of about $44.6, $42.7 $, and $50.4 for deterministic, stochastic, and robust planning are obtained, respectively. Moreover, considering function priority has a significant impact on the final results.

Automated summary

This paper proposes a scenario-based assessment strategy for optimal hub scheduling by considering uncertain parameters and CCUS technology, aiming to minimize cost and pollution. Three planning horizons are investigated, and the problem is modeled as RMIP and solved in GAMS software. Results show that utilizing CCUS technology effectively reduces costs and pollution.