Optimization of DG with Enhanced Elephant Herding Optimization in Distribution Network

Conventional and Non-Conventional Centralized power plants far from populations are utilized to generate electric power and this electric power transmits from generating stations to distribution stations over long distance. Distribution systems are generally radial and ring type. The use of radial distribution systems (RDS) is popular because they are straightforward, affordable, and only rely on a single feeder for supply when something goes wrong. Due to the unidirectional flow of electricity in RDS and the large r/x(resistance/reactance) ratio, huge voltage drops, poor Voltage Stability, and significant energy loss occur. Distributed Generation (DG) is installed in the distribution network at the customer's end, but correct installation is necessary to maximize its size and allocation. Meta-heuristic techniques are applied to get solution of the optimize problem of DG site and size. Single as well as Multi-objective problem can be solved using meta-heuristic artificial intelligence techniques such as Enhanced Elephant Herding Optimization (EEHO) by using a load flow technique (Newton Raphson method) for placing small generating units in the distribution system. A Meta heuristic algorithm Elephant herding optimization (EHO) is based on herding behavior of elephants. Enhanced Elephant herding optimization (EEHO) is modified phase of EHO to improve inappropriate divergence towards origin of clan and improve its exploration and extraction aptitude by updating both clan and separating operators.