Adaptive Embedded Clonal Evolutionary Programming for optimal DG installation

Nowadays, Distributed Generation (DG) has become more popular as a viable element of electric power systems. DG was designed as a small scale generation sources in order to locate at or near load center. The installation of DG is usually deployed within the distribution system to get the positive impacts such as reducing power losses, enhancing voltage profiles, differing costly for upgrading process, and reducing transmission and distribution network congestion. The purpose of this paper is to present a new technique namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). The objective of the study is to employ AECEP optimization technique for loss minimization and voltage profile monitoring. This technique was developed to optimally determine the location and sizing of DG for the same purpose. Test was performed on the IEEE 69-Bus RDS for several cases in terms of loading conditions. The proposed AECEP was implemented for single DG and two DGs installation. The result of the proposed AECEP technique was found in a good agreement with those obtained from the EP and AIS in terms of loss minimization and voltage profile improvement.