Towards optimum macro-sitting of wind farms in the Greek power supply system using Generalized Evolutionary Algorithms

摘要: To meet the wind energy national targets, effective implementation of massive wind power installed capacity into the power supply system is required. In such a perspective, the wind capacity credit and the effective absorption of wind energy production are two of the most important technological issues. The effect of spatial dispersion of wind power installations within a very wide area (eg national level) on the two above mentioned issues should be accounted for. The whole approach is based on probability theory and makes use of wind forecasting models to represent the wind energy potential over any candidate area for future wind farm installations in the country. Additionally, the Generalized Evolutionary Algorithm EASY created in the laboratory of thermal turbomachines at NTUA, has been used to define the optimum solution of wind installed capacity in the several candidate macro-sites in the Greek power supply system. Results show that the spatial dispersion of wind power plants contributes beneficially to the wind capacity credit and the wind energy penetration levels into the power system.