Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system

Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and system loss increment. A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). Consequently, EDEP was for solving optimizations problem in power system through the tap changer optimizations scheme. Results obtained from this study are significantly superior compared to the traditional EP with implementation on the IEEE 30-bus reliability test system (RTS) for the loss minimization scheme