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Hybrid Artificial Immune System-firefly Algorithm Technique for Optimal DG Capacity and Operational Strategy in Distribution System

This paper presents a study on hybrid optimization technique for optimal distributed generation (DG) capacity and operational strategy in distribution system. In this study, hybrid method namely Artificial Immune System-Firefly Algorithm (AISFA) is developed to determine the optimal size of the schemes respectively in the distribution system. The Firefly Algorithm (FA) which is a type of meta-heuristic algorithm is inspired by the blinking or flashing behaviour of fireflies that is embedded into Artificial Immune System (AIS) algorithm. The aim of this study is to develop the AISFA algorithm in order to improve the voltage profile and minimize losses of distribution system between the different operational strategy and types of DG. The types of DG include DG type 1, DG type 2, and DG type 3. The proposed technique was verified on IEEE 69-bus test system and the program was developed using the MATLAB programming software. The results showed a significant loss reduction in the line losses and voltage profile improvement has been obtained for optimal DG capacity and operational strategy in distribution system. From the simulation, the results were recorded in terms of the total losses and minimum voltage for the system. The results of the optimisation process of DG are utilized for the assistance of power system operators and planners. The power system planner can adopt the suitable sizes and locations from the obtained result for the planning of utility in term of economic and geographical consideration.