Optimization of a cryogenic liquid air energy storage system and its optimal thermodynamic performance

储能 气体压缩机 涡轮机 液化 等熵过程 可用能 工艺工程 总压比 可再生能源 核工程 火用 工程类 环境科学 功率(物理) 机械工程 热力学 电气工程 物理 岩土工程
作者
Hongbo Tan,Na Wen,Zhi Ding,Yanzhong Li
出处
期刊:International Journal of Energy Research [Wiley]
卷期号:46 (11): 15156-15173 被引量:4
标识
DOI:10.1002/er.8214
摘要

For grid-scale intermittent electricity storage, liquid air energy storage (LAES) is considered to be one of the most promising technologies for storing renewable energy. In this study, a steady-state process model was developed for an LAES, by combining a Linde liquefaction process and an open Rankine power cycle. To investigate the system performance and achieve global optimization, a single-factor analysis approach and multifactor genetic algorithm (GA) optimization model were built using MATLAB software. The effects of the charging pressure, storage pressure, discharging pressure, and isentropic efficiency of the compressor/turbine on the LAES performance parameters, such as the inlet temperature of the Joule–Thomson valve, round-trip efficiency (RTE), liquefaction ratio (LR), and power consumptions in the compressor, cryo-pump, and turbine, were investigated. Subsequently, the optimal conditions were obtained using the GA optimization method to achieve the optimal performance of the LAES. The results showed that the charging pressure, discharging pressure, and isentropic efficiencies of the compressor and turbine had significant effects on the RTE; an increase in the discharging pressure resulted in an improved expansion power output; the GA optimization could achieve RTE, LR, the system energy storage and recovery exergy efficiencies of 53.33%, 86.96%, 81.00%, and 78.16%; the power consumption in the compressor of GA optimization was 10.02% maximum saving. The proposed optimization method can be used to further explore the global optimization of cryogenic energy storage systems, such as different-layout LAES systems and different cryogenic liquefaction media energy storage systems.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
chai发布了新的文献求助10
刚刚
刚刚
孙李貌发布了新的文献求助10
刚刚
小二郎应助zjy采纳,获得10
1秒前
BowieHuang应助末日的阳光采纳,获得10
1秒前
852应助宁灭龙采纳,获得20
1秒前
1秒前
Owen应助科研通管家采纳,获得10
1秒前
2秒前
hh完成签到,获得积分10
2秒前
天天快乐应助科研通管家采纳,获得10
2秒前
amberzyc应助科研通管家采纳,获得20
2秒前
zyjwf发布了新的文献求助10
2秒前
FashionBoy应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
研友_VZG7GZ应助科研通管家采纳,获得10
2秒前
2秒前
zhonglv7应助科研通管家采纳,获得10
2秒前
科研通AI6应助科研通管家采纳,获得10
2秒前
传奇3应助科研通管家采纳,获得10
2秒前
共享精神应助科研通管家采纳,获得30
2秒前
清心淡如水完成签到 ,获得积分10
2秒前
Orange应助科研通管家采纳,获得10
2秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
星辰大海应助科研通管家采纳,获得10
2秒前
2秒前
慕青应助科研通管家采纳,获得10
2秒前
科研通AI2S应助科研通管家采纳,获得30
3秒前
李健应助科研通管家采纳,获得10
3秒前
科研通AI6应助科研通管家采纳,获得10
3秒前
天天快乐应助科研通管家采纳,获得30
3秒前
无花果应助科研通管家采纳,获得10
3秒前
3秒前
科研通AI6应助科研通管家采纳,获得10
3秒前
peggypan108发布了新的文献求助10
3秒前
共享精神应助科研通管家采纳,获得10
3秒前
脑洞疼应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
高分求助中
Theoretical Modelling of Unbonded Flexible Pipe Cross-Sections 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
《药学类医疗服务价格项目立项指南(征求意见稿)》 880
花の香りの秘密―遺伝子情報から機能性まで 800
3rd Edition Group Dynamics in Exercise and Sport Psychology New Perspectives Edited By Mark R. Beauchamp, Mark Eys Copyright 2025 600
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
Digital and Social Media Marketing 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5620260
求助须知:如何正确求助?哪些是违规求助? 4704917
关于积分的说明 14929736
捐赠科研通 4761567
什么是DOI,文献DOI怎么找? 2550911
邀请新用户注册赠送积分活动 1513652
关于科研通互助平台的介绍 1474592