{"title":"Multi-objective optimisation of ORC–LNG systems using the novel One-shot Optimisation method","authors":"Han Zhang, Giovanna Cavazzini, Alberto Benato","doi":"10.1016/j.energy.2024.133629","DOIUrl":null,"url":null,"abstract":"<div><div>Optimisation is drawing more and more attention in the organic Rankine cycle (ORC) research field. However, as the complexity of the ORC scenarios increases, it poses challenges on operational parameter, working fluid, and configuration optimisation levels. This work first proposes an improved optimisation method, termed the One-shot Optimisation (OSO) method, which can simultaneously optimise the working fluid and configuration. Then, a two-objective optimisation is performed using the OSO method in combined ORC–LNG systems, considering up to eight operational parameters, 11 working fluids, and 16 system configurations to maximise energy efficiency and minimise the electricity production cost (EPC). Finally, the result of the optimisation is divided according to the thermodynamic weight (W<sub>1</sub>), and two typical conditions are analysed in detail: the maximum case (W<sub>1</sub> = 1) and the balanced case (W<sub>1</sub> = 0.5). The results show that the OSO method is capable of identifying the optimal working fluid and optimal configuration within a single optimisation process. The basic ORC configuration is preferred when W<sub>1</sub> is lower while the recuperative ORC is preferred when W<sub>1</sub> is higher. The balanced case can achieve an energy efficiency comparable to that of the maximum case but with a significantly lower EPC. The balanced case can achieve as much as 87. 48% of energy efficiency, requiring only 19.77% of the EPC compared to those of the maximum case.</div></div>","PeriodicalId":11647,"journal":{"name":"Energy","volume":"313 ","pages":"Article 133629"},"PeriodicalIF":9.0000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360544224034078","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Optimisation is drawing more and more attention in the organic Rankine cycle (ORC) research field. However, as the complexity of the ORC scenarios increases, it poses challenges on operational parameter, working fluid, and configuration optimisation levels. This work first proposes an improved optimisation method, termed the One-shot Optimisation (OSO) method, which can simultaneously optimise the working fluid and configuration. Then, a two-objective optimisation is performed using the OSO method in combined ORC–LNG systems, considering up to eight operational parameters, 11 working fluids, and 16 system configurations to maximise energy efficiency and minimise the electricity production cost (EPC). Finally, the result of the optimisation is divided according to the thermodynamic weight (W1), and two typical conditions are analysed in detail: the maximum case (W1 = 1) and the balanced case (W1 = 0.5). The results show that the OSO method is capable of identifying the optimal working fluid and optimal configuration within a single optimisation process. The basic ORC configuration is preferred when W1 is lower while the recuperative ORC is preferred when W1 is higher. The balanced case can achieve an energy efficiency comparable to that of the maximum case but with a significantly lower EPC. The balanced case can achieve as much as 87. 48% of energy efficiency, requiring only 19.77% of the EPC compared to those of the maximum case.
期刊介绍:
Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics.
The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management.
Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.