A number of load control techniques and technologies have already been developed for autonomous power systems but no single technique has been widely adopted. Many of these load control systems have been partially successful but have suffered from a number of limitations that were addressed as part of this project. This thesis describes the development of distributed intelligent load controllers designed to address the limitations of previous load control solutions. A self-tuning fuzzy controller was developed to improve the power quality and efficiency of autonomous renewable energy systems. A laboratory wind-diesel test rig was developed to aid the design and testing of the load controller hardware and software. Computer models of wind powered and wind-diesel powered networks were produced to enable the design and testing of distributed fuzzy load control algorithms. The load controllers were tested throughout the development process on four autonomous renewable energy systems: - A single phase 25kVA run of river micro-hydro system in Scotland - A wind only system in the UK, with a 60kW stall regulated wind turbine fitted with a synchronous generator - A 30kW micro-hydro system on the island of Rum in Scotland - A 93kW wind-diesel system at the Rutherford Appleton Laboratories in the UK which used a 45kW stall regulated wind turbine fitted with an induction generator. The site results were promising and showed that distributed intelligent load control is an effective technique for controlling autonomous renewable energy systems.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:550559 |
| Date | January 2001 |
| Creators | Taylor, Philip Charles |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.0024 seconds