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首页> 外文期刊>Renewable & Sustainable Energy Reviews >Comprehensive assessment and multi-objective optimization of a green concept based on a combination of hydrogen and compressed air energy storage (CAES) systems
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Comprehensive assessment and multi-objective optimization of a green concept based on a combination of hydrogen and compressed air energy storage (CAES) systems

机译:基于氢气压缩空气储能(CAES)系统的综合评估和多目标优化绿色概念

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摘要

In this paper, a novel efficient and environmentally-friendly hybrid energy production/storage system comprising a compressed air energy storage, a heliostat-driven Brayton cycle, and a hydrogen production unit is proposed and thoroughly investigated. The aim is to minimize the pollutant emission of compressed air energy storage technology while adequately addressing intermittency and electricity curtailment of power grids with high penetration of renewable sources. The proposed system uses the surplus power and wasted heat of the solar powered Brayton cycle to store pressurized air and hydrogen during off-peak periods, and releases them for extra power generation during peak demand periods. For the performance analysis of this hybrid solution, the reference system is precisely analyzed from thermodynamic and economic points of view. Then, training the results of the developed model employing an artificial neural network, four multi-objective optimization programs based on MOPSO, NSGA-II, PESA-II, and SPEA2 algorithms are performed to find an optimal trade-off between thermodynamic performance and economic attractiveness of the system. It is concluded that the system has an exergy round trip efficiency of 60.4% and a total cost rate of 117.5 $/GJ at the optimum solution. Applying the proposed method for the case study of Los Angeles with real historical data, 3313 ton/year Carbone-Dioxide emission is prevented, resulting in around 80,000 $/year environmental cost reduction. Also, the economic analysis indicates a payback period of shorter than 4.6 years for the system.
机译:本文提出并彻底研究了一种新型高效和环保的混合能量生产/存储系统,包括压缩空气储能,升降的空气能量存储,升降螺旋顿循环和氢生产单元。目的是最大限度地减少压缩空气储能技术的污染物排放,同时充分解决了高可再生源的电网间歇性和电网的间歇性和电力缩减。所提出的系统使用太阳能发电的布雷顿循环的剩余电力和浪费的热量,以在非高峰期间储存加压空气和氢气,并在峰值需求期间释放它们以进行额外的发电。对于该混合解决方案的性能分析,从热力学和经济观点精确分析了参考系统。然后,培训采用人工神经网络的开发模型的结果,进行了基于MOPSO,NSGA-II,PESA-II和SPEA2算法的四个多目标优化程序,以找到热力学性能和经济之间的最佳权衡系统的吸引力。得出结论,该系统的往返效率低于60.4%,最佳解决方案的总成本率为117.5美元/ GJ。应用拟议的方法对洛杉矶具有真正历史数据的洛杉矶,预防3313吨/年碳碳碳碳碳碳碳碳氧化碳排放量,导致约80,000美元的环境成本减少。此外,经济分析表明该系统短于4.6岁的投资回收期。

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