用混合制冷剂系统修改的峰值剃须能量存储系统的遗传算法优化
Seyyed Amirreza Abdollahi1, Arash Nourbakhsh Sadabad2, Seyed Amirreza Mousavi Alamdardehi3
1Faculty of Mechanical Engineering , University of Tabriz , Tabriz, Iran.
Scientific reports
|November 20, 2025
概括
这项研究优化了液化天然气 (LNG) 峰值剃须系统用于发电厂使用遗传算法. 优化的系统显著降低了能源消耗,并提供了强大的经济回报,提高了能源安全.
科学领域:
- 热力学和能源系统工程 热力学和能源系统工程
- 化学工程和工艺设计的过程设计.
- 计算优化和模拟的计算优化和模拟
背景情况:
- 在需求高峰期的天然气短缺,特别是冬季,挑战了发电可靠性.
- 季节性液化和储存天然气 (LNG) 为能源安全和减轻供应中断提供了解决方案.
- 现有的液化天然气峰值削减系统需要在各种发电厂应用中优化热力学和经济效率.
研究的目的:
- 设计和优化基于混合制冷剂 (MR) 的液化天然气 (LNG) 生产周期,用于峰值剃须应用.
- 开发一个综合热力学和经济绩效指标的多领域优化框架.
- 为了适应气体发电厂面临季节性燃料供应挑战的优化液化天然气循环.
主要方法:
- 利用基因算法 (GA) 与Aspen HYSYS模拟相结合,用于热力学建模和优化.
- 通过优化制冷剂成分,压力水平和流量,最大限度地降低了特定能耗 (SEC).
- 在优化框架内同时评估能量,功率和经济性能.
主要成果:
- 实现了12%的特定能源消耗 (SEC) 减少,将其从0.37降至0.31kWh/kg.
- 优化的系统表现出了37%的功率效率和2.4.4的性能系数 (COP).
- 经济可行性得到证实,净当前价值 (NPV) 为420万美元,内部收益率 (IRR) 为13.1%,回报期为6.5年.
结论:
- 拟议的基于GA的优化框架在技术上对液化天然气峰值清除系统有效.
- 优化的系统提供了一个经济可行的解决方案,用于提高发电中的能源安全.
- 该方法可适应在遇到季节性天然气供应挑战的发电厂中更广泛的部署.
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