As the proportion of total Generation by Renewable sources compared to non-Renewable sources increases, the relative inertial stability provided by large rotating generators in electricity grids is found to shrink and is not being replaced by sources such as photovoltaic and wind power, which are already known for their inherent variability. This leads to electricity Generation systems being less stable, less flexible, and less adequate in applications with a high diversity factor, and literature shows that the penetration of Renewable energy sources in distribution-Generation/microgrid system frequently presents several technical and economic challenges in their usual applications. This work examines how increased Renewable energy penetration impacts the distribution-Generation system and suggests approaches and measures for tackling the challenges that are associated with it.

The progression towards smart grids, integrating Renewable energy resources, has increased the integration of Distributed generators (DGs) into power distribution networks. However, several economic and technical challenges can result from the unsuitable incorporation of DGs in existing distribution networks. Therefore, optimal placement and sizing of DGs are of paramount importance to improve the performance of distribution systems in terms of power loss reduction, voltage profile, and voltage stability enhancement. This paper proposes a methodology based on Dragonfly Optimization Algorithm (DA) for optimal allocation and sizing of DG units in distribution networks to minimize power losses considering variations of load demand profile. Load variations are represented as lower and upper bounds around base levels. Efficiency of the proposed method is demonstrated on IEEE 33-bus and IEEE 69-bus radial distribution test networks. The results show the performance of this method over other existing methods in the literature.