Title :
Optimisation of electrical system for offshore wind farms via genetic algorithm
Author :
Zhao, M. ; Chen, Z. ; Blaabjerg, Frede
Author_Institution :
Inst. of Energy Technol., Aalborg Univ., Aalborg East
fDate :
6/1/2009 12:00:00 AM
Abstract :
An optimisation platform based on genetic algorithm (GA) is presented, where the main components of a wind farm and key technical specifications are used as input parameters and the electrical system design of the wind farm is optimised in terms of both production cost and system reliability. The power losses, wind power production, initial investment and maintenance costs are considered in the production cost. The availability of components and network redundancy are included in the reliability evaluation. The method of coding an electrical system to a binary string, which is processed by GA, is developed. Different GA techniques are investigated based on a real example offshore wind farm. This optimisation platform has been demonstrated as a powerful tool for offshore wind farm design and evaluation.
Keywords :
costing; genetic algorithms; offshore installations; power generation reliability; wind power plants; binary string coding method; electrical system optimisation; genetic algorithm; maintenance cost; offshore wind farm; power loss; production cost; system reliability evaluation; wind power production;
Journal_Title :
Renewable Power Generation, IET
DOI :
10.1049/iet-rpg:20070112