Energy scheduling for grid connected wind farm systems

Wind energy is found to be a huge power resource ever since the time human civilization has evolved. Its importance has increased manifold as fossil fuel resources are depleting off quickly. However, the availability and variability of wind energy resource poses a high degree of hindrance to their integration into power grids leading to various power issues such as, deregulation of supply - load balance, introduction of harmonic currents into system, power system stability problems, etc. In this paper Artificial Neural Network based Yearly Auto - Regressive (ANNYAR) model is used for wind speed predictions. Predictions as obtained may be helpful to find out the optimal wind farm power integration schedule. A comparison has been done between the actual working schedule of wind farm and proposed schedule using predicted data for short - cum - medium term time horizon (i.e., 6, 12, 24, 48, 72 and 96 hours).