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

机译:基于情景的评估,用于在双重不确定性下,通过考虑CCU技术的多载体集线能源系统的最佳规划

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摘要

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.
机译:本文通过考虑不确定参数(电力价格和风力涡轮机输出功率)和同时的碳捕获利用率和储存(CCUS)技术,提供了一种基于方案的评估策略。 CCUS技术一方面有助于克服污染问题,另一方面赚取电力系统的收入。研究了三种不同的规划视野,包括确定性,随机和强大的模型进行了比较。能源枢纽(EH)旨在同时尽量减少总成本和环境污染,同时考虑目标职能优先的效果。然后将问题建模为真实的混合整数编程(RMIP),并使用CPLEX在GAMS软件中解决;结果与其他溶剂相比。 epsilon约束(EPC)方法和模糊满足方法用于基于所呈现的模型选择最佳解决方案。最后,执行灵敏度分析。结果表明,通过利用CCU技术,所有计划视野的成本和污染都会正确降低。 CCUS的利润分别获得约44.6美元,42.7美元和50.4美元,用于确定性,随机和强大规划。此外,考虑到功能优先权对最终结果产生重大影响。

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