Immune-Commensal-Evolutionary Programming for solving non-smooth/non-convex economic dispatch problem

Abstract

This paper presents the development of a new hybrid optimization technique termed as Immune-Commensal-Evolutionary Programming (ICEP) and its implementation to solve non-smooth/ non-convex Economic Dispatch (ED) problem. ICEP is developed with the objective to overcome the drawbacks of single optimization techniques like evolutionary programming (EP), Artificial Immune System (AIS) and Symbiotic Organisms Search (SOS). The idea of developing this ICEP technique is to gather the strengths from the three single optimization techniques: EP, AIS and SOS to form a new hybrid technique that can solve non-smooth/ non-convex ED problem accurately. This hybrid technique has better performance in finding the global optima of non-smooth/ non-convex ED problem compared to the single optimization techniques. The typical drawback of the single optimization techniques is immature convergence, especially EP and AIS techniques. ICEP can avoid this from happening by thoroughly directing the searching process to its global optima. The proposed ICEP technique has been tested on the IEEE 30-Bus Reliability Test System (RTS) and IEEE 57-Bus Reliability Test System (RTS) with three case studies. It is found that ICEP is superior than EP and AIS in producing better non-smooth/ non-convex ED solution.

Keywords

• Economic dispatch
• Evolutionary programming
• Artificial immune system
• Symbiotic organism search
• Valve-point loading effect
• Non-smooth