The Imperialist Competitive Algorithm for Optimal Multi-Objective Location and Sizing of DSTATCOM in Distribution Systems Considering Loads Uncertainty

The optimal location and sizing of distribution static compensator (DSTATCOM) in distribution systems is a complex nonlinear problem. This problem is constrained by various technical limits and can offer different objectives that would provide many benefits to the network. These include minimization of power losses, index of voltage profile, load balancing index, and annual cost saving index which have been considered in this paper. In the present work, the Imperialist Competitive Algorithm (ICA) is employed for optimizing the distribution systems where an optimal location and sizing of DSTATCOM is investigated. In this study, an aggregating operator named Max-geometric mean is used for combination of objectives and providing overall objective function. The scaling of objectives is performed in the fuzzy framework. The proposed algorithm is implemented in 33 and 69 buses IEEE test systems. Furthermore, the uncertainty of the loads of the balanced system is modeled by using a fuzzy technique. Based on the numerical results of this work, one can extract that the performance of the ICA is slightly higher than other meta-heuristic algorithms; hence the introduced approach can be used by utility services for optimal DSTATCOM allocation and sizing in the distribution systems.