Maximizing the accommodation of distributed wind power generation

Wind power is the fastest growing renewable power source worldwide. The maximization of its deployment in a given network has to consider the inherent variability of the resource while strategically minimizing potential drawbacks and fulfilling technical requirements. In this work, a steady-state analysis considering the assessment of energy exports to the grid, losses and short-circuit levels is proposed, while taking into account time-varying loads and generation, and satisfying voltage and thermal limits. A multiobjective programming approach, based on the nondominated sorting genetic algorithm (NSGA), has been developed to find a set of optimal connection points for such purpose. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the United Kingdom.