  Within the last 20 years, wind turbines have reached matured and the growing
worldwide wind energy market will allow further improvements. In the recent
decades, the numbers of research papers that have applied optimization
techniques in the attempt to obtain an optimal design have increased. The main
target of manufacturers has been to minimize the cost of energy of wind
turbines in order to compete with fossil-fuel sources. Therefore, it has been
argued that it is more stimulating to evaluate the wind turbine design as an
optimization problem consisting of more than one objective. Using
multi-objective optimization algo- rithms, the designers are able to identify a
trade-off curve called Pareto front that reveals the weaknesses, anomalies and
rewards of certain targets. In this chapter, we present the fundamental
principles of multi-objective optimization in wind turbine design and solve a
classic multi-objective wind turbine optimization problem using a genetic
algorithm.
