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Parametric Optimisation of a Trigenerative Small Scale Compressed Air Energy Storage System^{ †}

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## Abstract

**:**

## 1. Introduction

## 2. Methodology

- Air is considered as an ideal gas.
- The pressure losses in HEX of discharge phase are neglected compared with the losses in HEX of discharge phase.
- The air input temperature of the first HEX in the discharge phase is considered at the ambient temperature.
- The temperature of the cold TES reservoir in the charging phase is at the ambient temperature.

_{e,optimal}corresponds to the maximum input temperature of each turbine. Hence, N

_{e,optimal}is the minimum number of stages, which can satisfy the above condition and it can be found by an iteration procedure. This makes a good contribution to relate the number of expansion stages to the compression stages and other design parameters.

## 3. Results and Discussions

#### 3.1. Effect of Hot TES Temperature

_{e}decreases at some critical values as T

_{h,TES}increases, while the system efficiencies increases too slowly only on the basis of these values. This is due to the fact that the input temperature of each turbine stage and subsequently the preheating energy changes only at the critical values of T

_{h,TES}in order to satisfy the condition of an output expansion stage temperature equals of the ambient.

_{e}, the HEX footprints of the discharging phase decrease substantially (Figure 3) since the logarithmic mean temperature LMTD grows, assigned to the rise of the water output temperature of TES (Figure 2). The maximum values of HEX footprints are achieved at the critical values of hot, TES with a general declining trend due to the decrease of N

_{e}. The variation of the total footprint follows that of the discharging phase HEX footprints tendency given the small rise of the HEX footprints of the charging phase.

_{h,TES}are between 110 and 120 °C or between 140 and 150 °C.

#### 3.2. Effect of the Maximum Storage Pressure

## 4. Conclusions

- T
_{h,TES}has a minor effect on the system performances, whereas it must be chosen such that to minimize the number of expansion stages and heat exchangers footprints. - The maximum storage pressure plays a leading role on the system efficiency and energy density.
- For microscale applications, the system suffers from low performances which is attributed to the poor performances of existing micro-scale machinery.

## Author Contributions

## Acknowledgments

## Conflicts of Interest

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**Figure 2.**T-CAES efficiencies and the optimal number of expansion stages (

**left**) and the temperature output of AM and of the cold TES (

**right**) as a function of the temperature of hot TES.

**Figure 4.**Discharge to charge time ratio and energy density as a function of the maximum storage pressure.

**Figure 5.**T-CAES efficiencies and the total HEX footprints as a function of the maximum storage pressure.

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**MDPI and ACS Style**

Cheayb, M.; Poncet, S.; Marin-Gallego, M.; Tazerout, M.
Parametric Optimisation of a Trigenerative Small Scale Compressed Air Energy Storage System. *Proceedings* **2019**, *23*, 5.
https://doi.org/10.3390/proceedings2019023005

**AMA Style**

Cheayb M, Poncet S, Marin-Gallego M, Tazerout M.
Parametric Optimisation of a Trigenerative Small Scale Compressed Air Energy Storage System. *Proceedings*. 2019; 23(1):5.
https://doi.org/10.3390/proceedings2019023005

**Chicago/Turabian Style**

Cheayb, Mohamad, Sébastien Poncet, Mylène Marin-Gallego, and Mohand Tazerout.
2019. "Parametric Optimisation of a Trigenerative Small Scale Compressed Air Energy Storage System" *Proceedings* 23, no. 1: 5.
https://doi.org/10.3390/proceedings2019023005