{"title":"利用确定性数学模型优化液态空气储能系统","authors":"","doi":"10.1016/j.est.2024.113940","DOIUrl":null,"url":null,"abstract":"<div><div>Liquid air energy storage (LAES) systems are a promising technology for storing electricity due to their high energy density and lack of geographic constraints. However, some LAES systems still have relatively low round-trip efficiencies. This work aims to improve LAES system performance through optimization strategies.</div><div>Deterministic non-linear mathematical models were implemented in an object-oriented equation-based programming language. An optimization algorithm was applied to the LAES system. The model was designed to facilitate the removal of components and find novel configurations, despite not incorporating discrete decisions (binary variables). After successful verification, the model was used to maximize round-trip efficiency. Compared to the base case, the round-trip efficiency and liquid air yield increased by approximately 63 % and 48 %, respectively. The optimal solution obtained had an impact on the LAES system structure, eliminating a heat exchanger in the cold box compared to the base case and resulting in a new system configuration. The proposed mathematical model is a valuable tool for decision-making in optimizing LAES systems, effectively simulating and optimizing these systems. This work represents an advance in mathematical modeling from the perspective of Process System Engineering (PSE). It showcases the application of simultaneous optimization, derivative-based algorithms, and rigorous property package estimation through dynamic link libraries to optimize a LAES system.</div></div>","PeriodicalId":15942,"journal":{"name":"Journal of energy storage","volume":null,"pages":null},"PeriodicalIF":8.9000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of liquid air energy storage systems using a deterministic mathematical model\",\"authors\":\"\",\"doi\":\"10.1016/j.est.2024.113940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Liquid air energy storage (LAES) systems are a promising technology for storing electricity due to their high energy density and lack of geographic constraints. However, some LAES systems still have relatively low round-trip efficiencies. This work aims to improve LAES system performance through optimization strategies.</div><div>Deterministic non-linear mathematical models were implemented in an object-oriented equation-based programming language. An optimization algorithm was applied to the LAES system. The model was designed to facilitate the removal of components and find novel configurations, despite not incorporating discrete decisions (binary variables). After successful verification, the model was used to maximize round-trip efficiency. Compared to the base case, the round-trip efficiency and liquid air yield increased by approximately 63 % and 48 %, respectively. The optimal solution obtained had an impact on the LAES system structure, eliminating a heat exchanger in the cold box compared to the base case and resulting in a new system configuration. The proposed mathematical model is a valuable tool for decision-making in optimizing LAES systems, effectively simulating and optimizing these systems. This work represents an advance in mathematical modeling from the perspective of Process System Engineering (PSE). It showcases the application of simultaneous optimization, derivative-based algorithms, and rigorous property package estimation through dynamic link libraries to optimize a LAES system.</div></div>\",\"PeriodicalId\":15942,\"journal\":{\"name\":\"Journal of energy storage\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of energy storage\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352152X24035266\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of energy storage","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352152X24035266","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Optimization of liquid air energy storage systems using a deterministic mathematical model
Liquid air energy storage (LAES) systems are a promising technology for storing electricity due to their high energy density and lack of geographic constraints. However, some LAES systems still have relatively low round-trip efficiencies. This work aims to improve LAES system performance through optimization strategies.
Deterministic non-linear mathematical models were implemented in an object-oriented equation-based programming language. An optimization algorithm was applied to the LAES system. The model was designed to facilitate the removal of components and find novel configurations, despite not incorporating discrete decisions (binary variables). After successful verification, the model was used to maximize round-trip efficiency. Compared to the base case, the round-trip efficiency and liquid air yield increased by approximately 63 % and 48 %, respectively. The optimal solution obtained had an impact on the LAES system structure, eliminating a heat exchanger in the cold box compared to the base case and resulting in a new system configuration. The proposed mathematical model is a valuable tool for decision-making in optimizing LAES systems, effectively simulating and optimizing these systems. This work represents an advance in mathematical modeling from the perspective of Process System Engineering (PSE). It showcases the application of simultaneous optimization, derivative-based algorithms, and rigorous property package estimation through dynamic link libraries to optimize a LAES system.
期刊介绍:
Journal of energy storage focusses on all aspects of energy storage, in particular systems integration, electric grid integration, modelling and analysis, novel energy storage technologies, sizing and management strategies, business models for operation of storage systems and energy storage developments worldwide.