Distributed Energy Sources Management using Shuffled Frog-Leaping Algorithm for Optimizing the Environmental and Economic Indices of Smart Microgrid

When employing renewable energy within a smart micro grid (SMG), the management of distributed energy resources (DER) plays a crucial role in optimizing practical objectives of SMG. This study utilizes the Shuffled frog leaping algorithm (SFLA) to manage DER and implement demand response programs (DSP), aiming to optimize economic, technical and environmental problems of SMG. The modeling of renewable energy resources (RES) is a challenge due to its uncertainty, therefore, cumulative distribution function (CDF) is used for predicting the energy sources before its integration with SMG. The DER included in this study consists of the wind and solar energy, battery, micro turbine and the utility. This model is implemented in three different scenarios: a) basic grid operation, b) operation with maximum usage of renewable energy resources, c) operation with maximum usage of RES and DRP. The results obtained show the superiority of proposed SFLA algorithm in terms of avoiding pre-mature convergence which is a common challenge in optimization, and achieving global optimum for the proposed objectives. For validation, this model is implemented in MAT LAB considering different constraints.