Performance assessment of Adiabatic Compressed Air Energy Storage (A-CAES) power plants integrated with packed-bed thermocline storage systems

2017 ◽  
Vol 151 ◽  
pp. 343-356 ◽  
Author(s):  
Vittorio Tola ◽  
Valentina Meloni ◽  
Fabrizio Spadaccini ◽  
Giorgio Cau
Author(s):  
Sammy Houssainy ◽  
Reza Baghaei Lakeh ◽  
H. Pirouz Kavehpour

Human activity is overloading our atmosphere with carbon dioxide and other global warming emissions. These emissions trap heat, increase the planet’s temperature, and create significant health, environmental, and climate issues. Electricity production accounts for more than one-third of U.S. global warming emissions, with the majority generated by coal-fired power plants. These plants produce approximately 25 percent of total U.S. global warming emissions. In contrast, most renewable energy sources produce little to no global warming emissions. Unfortunately, generated electricity from renewable sources rarely provides immediate response to electrical demands, as the sources of generation do not deliver a regular supply easily adjustable to consumption needs. This has led to the emergence of storage as a crucial element in the management of energy, allowing energy to be released into the grid during peak hours and meet electrical demands. Compressed air energy storage can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. Most compressed air energy storage systems run at very high pressures, which possess inherent problems such as equipment failure, high cost, and inefficiency. This research aims to illustrate the potential of compressed air energy storage systems by illustrating two different discharge configurations and outlining key variables, which have a major impact on the performance of the storage system. Storage efficiency is a key factor to making renewable sources an independent form of sustainable energy. In this paper, a comprehensive thermodynamic analysis of a compressed air energy storage system is presented. Specifically, a detailed study of the first law of thermodynamics of the entire system is presented followed by a thorough analysis of the second law of thermodynamics of the complete system. Details of both discharge and charge cycles of the storage system are presented. The first and second law based efficiencies of the system are also presented along with parametric studies, which demonstrates the effects of various thermodynamic cycle variables on the total round-trip efficiency of compressed air energy storage systems.


2020 ◽  
Vol 269 ◽  
pp. 115132 ◽  
Author(s):  
Zhirong Liao ◽  
Hua Zhong ◽  
Chao Xu ◽  
Xing Ju ◽  
Feng Ye ◽  
...  

2013 ◽  
Vol 448-453 ◽  
pp. 2786-2789 ◽  
Author(s):  
Jin Li ◽  
Chu Fu Li ◽  
Yan Xia Zhang ◽  
Hui Guo Yue

Nuclear plants are facing more and more peaking pressure, and combined operation with compressed air energy storage (CAES) systems is an effective approach to improve its peaking capacity. This work first simulates and conducts the exergy analysis for the CAES system. The results show that exergy efficiency of the CAES system is about 51.7%, as well as the exergy loss are primary in the fuel combustion and compressed air cooling processes, accounted for 25.4% and 11.3% of total exergy, respectively. Subsequently, three combined operation modes between CAES system and nuclear power plants for power grid peaking are investigated, which shows that three section tracking mode and incomplete tracking mode can achieve the balance between peaking effects and peaking cost.


Author(s):  
Robert Schainker ◽  
Michael Nakhamkin ◽  
John R. Stange ◽  
Louis F. Giannuzzi

Results of engineering and optimization of 25 MW and 50 MW turbomachinery trains for compressed air energy storage (CAES) power plant application are presented. Submitted by equipment suppliers, proposals are based on the commercially available equipment. Performance data and budget prices indicate that the CAES power plant is one of the most cost effective sources of providing peaking power and load management.


Energy ◽  
2022 ◽  
Vol 244 ◽  
pp. 122993
Author(s):  
Huan Guo ◽  
Yujie Xu ◽  
Yilin Zhu ◽  
Xuezhi Zhou ◽  
Haisheng Chen

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