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Maximum power point tracking of a small-scale compressed air energy storage system

Maximum power point tracking of a small-scale compressed air energy storage system
Maximum power point tracking of a small-scale compressed air energy storage system
The thesis is concerned with a small-scale compressed air energy storage (SS-CAES) system. Although these systems have relatively low energy density, they offer advantages of low environmental impact and ease of maintenance.

The thesis focuses on solving a number of commonly known problems related to the perturb and observe (P&O) maximum power point tracking (MPPT) system for SS-CAES, including confusion under input power fluctuation conditions and operating point dither.

A test rig was designed and built to be used for validation of the theoretical work. The rig comprised an air motor driving a permanent magnet DC generator whose power output is controlled by a buck converter. A speed control system was designed and implemented using a dSPACE controller. This enabled fast convergence of MPPT.

Four MPPT systems were investigated. In the first system, the air motor characteristics were used to determine the operating speed corresponding to MPP for a given pressure. This was compared to a maximum efficiency point tracking (MEPT) system. Operating at the maximum power point resulted in 1% loss of efficiency compared to operating at the maximum efficiency point. But MPPT does not require an accurate model of the system that is needed for MEPT, which also requires more sensors.

The second system that was investigated uses a hybrid MPPT approach that did not require a prior knowledge system model. It used the rate of change of power output with respect to the duty cycle of the buck converter as well as the change in duty cycle to avoid confusion under input power fluctuations. It also used a fine speed step in the vicinity of the MPP and a coarse speed step when the operating point was far from the MPP. Both simulation and experimental results demonstrate the efficiency of this proposed system.

The third P&O MPPT system used a fuzzy logic approach which avoided confusion and eliminated operating point dither. This system was also implemented experimentally.
A speed control system improved the controllable speed-range by using a buck-boost converter instead. The last MPPT system employed a hybrid P&O and incremental inductance (INC) approach to avoid confusion and eliminate operating point dither. The simulation results validate the design.

Although the focus of the work is on SS-CAES, the results are generic in nature and could be applied to MPPT of other systems such as PV and wind turbine.
Kokaew, Vorrapath
c9423a98-81d2-4293-bcc3-891445f3de92
Kokaew, Vorrapath
c9423a98-81d2-4293-bcc3-891445f3de92
Moshrefi-Torbati, Mohamed
65b351dc-7c2e-4a9a-83a4-df797973913b

(2016) Maximum power point tracking of a small-scale compressed air energy storage system. University of Southampton, Faculty of Engineering and the Environment, Doctoral Thesis, 196pp.

Record type: Thesis (Doctoral)

Abstract

The thesis is concerned with a small-scale compressed air energy storage (SS-CAES) system. Although these systems have relatively low energy density, they offer advantages of low environmental impact and ease of maintenance.

The thesis focuses on solving a number of commonly known problems related to the perturb and observe (P&O) maximum power point tracking (MPPT) system for SS-CAES, including confusion under input power fluctuation conditions and operating point dither.

A test rig was designed and built to be used for validation of the theoretical work. The rig comprised an air motor driving a permanent magnet DC generator whose power output is controlled by a buck converter. A speed control system was designed and implemented using a dSPACE controller. This enabled fast convergence of MPPT.

Four MPPT systems were investigated. In the first system, the air motor characteristics were used to determine the operating speed corresponding to MPP for a given pressure. This was compared to a maximum efficiency point tracking (MEPT) system. Operating at the maximum power point resulted in 1% loss of efficiency compared to operating at the maximum efficiency point. But MPPT does not require an accurate model of the system that is needed for MEPT, which also requires more sensors.

The second system that was investigated uses a hybrid MPPT approach that did not require a prior knowledge system model. It used the rate of change of power output with respect to the duty cycle of the buck converter as well as the change in duty cycle to avoid confusion under input power fluctuations. It also used a fine speed step in the vicinity of the MPP and a coarse speed step when the operating point was far from the MPP. Both simulation and experimental results demonstrate the efficiency of this proposed system.

The third P&O MPPT system used a fuzzy logic approach which avoided confusion and eliminated operating point dither. This system was also implemented experimentally.
A speed control system improved the controllable speed-range by using a buck-boost converter instead. The last MPPT system employed a hybrid P&O and incremental inductance (INC) approach to avoid confusion and eliminate operating point dither. The simulation results validate the design.

Although the focus of the work is on SS-CAES, the results are generic in nature and could be applied to MPPT of other systems such as PV and wind turbine.

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Published date: December 2016
Organisations: University of Southampton, Mechatronics

Identifiers

Local EPrints ID: 404178
URI: http://eprints.soton.ac.uk/id/eprint/404178
PURE UUID: 944c58ef-790b-4a58-a059-4b6688dcd4bd

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Date deposited: 03 Jan 2017 14:54
Last modified: 28 Mar 2018 04:02

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Contributors

Thesis advisor: Mohamed Moshrefi-Torbati

University divisions

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