Integrated Grasshopper Algorithm-Evolutionary Programming Technique for Distributed Energy Resources Allocation

Distributed energy resources (DER) are among important components or additional supplies to an existing power system network. Its installation in an existing power system network will help improve the voltage level in a system, reduce current values through the transmission lines and reduce the total transmission loss. The sizing and locations for the installation of DER or distributed generation (DG) require optimal values. Otherwise, the system will experience either over-compensation or under-compensation phenomena. Thus, a reliable optimization technique is a crucial factor. Several optimization techniques are not reliable enough as they cannot reach optimal solutions and sometimes, they are not accurate. This paper presents a new optimization technique termed Integrated Grasshopper Evolutionary Programming Technique (IGEPT). IGEPT integrates some operators in the grasshopper optimization into the original evolutionary programming (EP). It was validated on the IEEE 30-Bus Reliability Test System (RTS) for voltage maximization effort as the objective function. Several cases were taken into account so as to highlight the robustness of this technique. A comparative study with other techniques is also conducted, which highlights the merit of IGEPT.