scholarly journals Advanced Adiabatic Compressed Air Energy Storage design and modelling accounting for turbomachinery performance

2021 ◽  
Vol 2116 (1) ◽  
pp. 012088
Author(s):  
J Roncolato ◽  
G Zanganeh ◽  
P Jenny ◽  
M Scholtysik ◽  
E Jacquemoud ◽  
...  

Abstract Energy storage plants are going to become a strategic asset in electric grids. This statement is confirmed looking at the increasing shares of renewables composing the energy portfolio of several nations. Therefore the power demand and production mismatches, caused by the intermittent nature of renewables, must be reconciled. Many energy storage solutions are available but Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) plants have potentials similar to pumped hydro systems (PHS). A physical model was developed in Matlab-Simscape to simulate the dynamics of AA-CAES plants, implementing temperature-dependent air properties, efficiency maps for turbomachinery and realistic power ramps. Furthermore, start-up and shut-down phases and energy consumption during idle periods were accounted for. The model embeds a 1D Fortran code to model the detailed behaviour of a packed-bed TES. The grid-to-grid performance of an AA-CAES plant was determined and the assumptions implemented to take into account real turbomachinery behaviour are presented.

Author(s):  
I. Arsie ◽  
V. Marano ◽  
G. Nappi ◽  
G. Rizzo

After a general overview of Hybrid Power Plants (HPP) and Compressed Air Energy Storage (CAES), the authors present a thermo-economic model for the simulation and optimization of a HPP consisting of a wind turbine coupled with CAES. In the proposed scheme, during periods of excess power production, atmospheric air is compressed in a multistage compressor and cooled; when there is power demand, the compressed air is heated in multiple expansion stages using the stored heat and conventional thermal sources. Such plants can offer significant benefits in terms of flexibility in matching a fluctuating power demand, particularly when renewable sources, characterized by high and often unpredictable variability, are utilized. The possible advantages in terms of energy and cost savings with respect to other solutions must be carefully assessed, critically depending on performance and efficiencies of each sub-system, most of them operating in transient and off-design conditions. To this purpose, a thermodynamic model composed of several sub-systems describing wind turbine, multi-stage compressor, intercooler, aftercooler, heat recovery system, compressed air storage and turbine has been developed in Matlab/Simulink® environment. In the paper, several scenarios are compared by simulation and optimization analysis and a parametric study of the plant performance with respect to the main design variables is presented.


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

2014 ◽  
Author(s):  
Huisheng Zhang ◽  
Dengji Zhou ◽  
Di Huang ◽  
Xinhui Wang

With the growing need for the use of electricity, power plants sometimes cannot generate enough power during the high demand periods. Thus various methods are introduced to solve this situation. Compressed air energy storage (CAES) technology seems to be a good solution to both peaking power demand and intermittent energy utilization transformed from renewable energy source like wind energy. Utilization of heat generated from the air compression process is a crucial problem of this technology. A compressed air energy storage system, with humid air as working fluid, is designed in this paper. In this system, heat of compressing air is transformed to the latent heat of water vapour, decreasing the power consumption of compressor and increasing energy generated per volume of storage. A Compressed Humid Air Energy Storage (CHAES) system model is established in this paper to simulate the performance of this system. Then the performance of this new system is evaluated by comparison to conventional CAES system, based on the simulation result. The result of this paper confirm the growing interest to CAES as a solution to peaking power demand and intermittent energy utilization, and indicates that CHAES system, as a great improvement of CAES system, has huge potential in the future.


2019 ◽  
Vol 6 ◽  
pp. 56-72
Author(s):  
Simon Tan ◽  
Andrew Wahlen

Compressed Air Energy Storage (CAES) has demonstrated promising potential for widescale use in the power distribution network, especially where renewables are concerned.Current plants are inefficient when compared to other technologies such as battery and pumped hydro. Presently, the greatest round-trip efficiency of any commercial CAES plant is 54% (McIntosh Plant), while the highest energy efficiency of any experimental plant is 66-70% (ADELE Project). So far, Adiabatic CAES systems have yielded promising results with round-trip efficiencies generally ranging between 65-75%, with some small-scale system models yielding round-trip efficiencies exceeding 90%. Thus far, minimal research has been devoted to analysing the thermodynamic effects of the thermal energy storage (TES) insulation. This metastudy identifies current industry and research trends pertaining to ACAES with a focus on the TES insulation supported by model simulations. Charged standby time and insulation of the TES on overall system efficiency was determined by performing a thermodynamic analysis of an ACAES system using packed bed heat exchangers (PBHE) for TES. The results provide insight into the effect various insulators, including concrete, glass wool and silica-aerogel, have on exergy loss in the TES and overall system efficiency. TES insulation should be carefully considered and selected according to the expected duration of fully charged standby time of the ACAES system. Keywords: Compressed air energy storage; adiabatic compressed air energy storage; thermal energy storage; thermodynamic efficiency; renewable energy storage, packed bed heat exchanger


2015 ◽  
Vol 155 ◽  
pp. 804-815 ◽  
Author(s):  
Edward Barbour ◽  
Dimitri Mignard ◽  
Yulong Ding ◽  
Yongliang Li

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