Introduction

Renewable energy generation and storage are of immense interest today because of their sustainability and their environmentally

friendly nature with little or no waste products. Due to its compatibility, long life cycle and low maintenance, a small scale

compressed air energy storage (SS-CAES) system has already been integrated with other sources of renewable energy for not only

supplementing and matching peak demand but also for improving output power quality [1]. The focus of this work is a stand-

alone pneumatic to electrical energy conversion SS-CAES with maximum power point tracking (MPPT) control for achieving

improved efficiency.

Power Management of a Stand-Alone,

Small-Scale Compressed Air Energy

Storage System (SS-CAES)

V. Kokaew, M. Moshrefi-Torbati and S.M. Sharkh

www.soton.ac.uk/engineering/research/groups/electromech.page | email:vk3e10@soton.ac.uk

Electro-Mechanical Engineering Group , Faculty of Engineering and Environment, University of Southampton, SO17 1BJ, UK

Aims & Objectives

A real-time MPPT algorithm is implemented experimentally in a

SS-CAES discharge system that does not require a priori

knowledge of the air motor characteristics or the use of a

pressure transducer. It employs a hybrid approach using two

search criteria for improving system dynamic. In this system, an

air motor is used to drive a DC-generator. The pneumatic-

electrical energy conversion is controlled to deliver resistive

power using a buck converter. The system is analysed using a

small signal model. A digital speed regulator is designed to

control the output power of the DC generator such that the

desired MPPT is achieved.

Methodology

The MPPT controller uses a

hybrid perturb and observe

search algorithm. It utilizes the

power-speed-pressure surface

when it is near the MPP (fine

tuning) to improve accuracy of

the search algorithm with small

speed step changes. When it is

far from the MPP, it uses coarse

speed step changes to increase

speed of convergence.

Fig 1. Configuration of the proposed discharging process with MPPT

Fig 2. Power-speed-pressure characteristic of

the air motor with two search criteria

Experimental Results

Fig 4. shows the experimental results of hybrid-MPPT

algorithm. In the speed versus time graph, the

optimal speed red curve is the speed at which the

power is maximum for a given pressure as

calculated from the air motor characteristics[2]. The

green speed curve is the demand speed calculated

by the proposed algorithm, and the black speed

curve is the actual measured speed. As can be seen,

following a short transient, the MPPT algorithm has

successfully produced correct speed demands in

response to changes in pressure.

References

[1] V. Kokaew, M. Moshrefi-Torbati and S. M. Sharkh, “Simulation of a

Solar Powered Air Compressor,” in 10th EEEIC Conference on

Environment and Electrical Engineering, Rome, 2011.

[2] V. Kokaew, M. Moshrefi-Torbati and S. M. Sharkh, "Maximum

Efficiency or Power Tracking of Stand-Alone Small Scale Compressed Air

Energy Storage System," Energy Procedia, vol. 42, pp. 387-396, 2013.

Fig 3. Experimental rig for the discharging process with

MPPT algorithm in a stand-alone system

Fig 4. Experimental result obtained using

the propose MPPT-algorithm

Conclusions

The real-time tracking of maximum power for a SS-CAES system was

investigated via the design and implementation of a P&O MPPT

algorithm. Using a hybrid search criteria, the algorithm can achieve a

short dynamic period in response to pressure fluctuations in the

compressed air. Future work will investigate the power management of

a hybrid storage device for a variable output load as shown in Fig 5.

Fig 5. Configuration of future work of

Power Management of SS-CAES