A Novel Tunicate Swarm Algorithm for Optimal Integration of Renewable Distribution Generation in Electrical Distribution Networks Considering Extreme Load Growth

In recent years, the addition of renewable-based distribution generation (DG) into the electrical distribution system has accelerated. The power requirements at the load centre can be met more efficiently by distributed generation (DG) than by the conventional power system. DG installation provides many technical benefits which include lower distribution losses, lower voltage stability index, and improved voltage profile. In electrical distribution networks, loads are typically expressed as a constant power (CP) load model, which is not considered realistic. For realistic load modeling of the radial distribution system, optimum load mix is represented as combination of different load models. Because the R/X ratio is so large in radial distribution systems, real power losses are a major concern. This paper presents a tunicate swarm algorithm (TSA) optimization technique for optimal DG installation with various load models and load growth for improved voltage profile, network losses reduction, and voltage stability index. The minimising of real power losses is utilised as a criterion for determining the best location and size of DG in this work. The results validate the effectiveness of DG integration, as well as the influence of various load models on the distribution system considering load growth. The proposed algorithm is tested on IEEE 33 bus distribution system and results shows that TSA outperforms existing optimization algorithms published in recent state-of-art literature.