Optimum Location of DG for Loss Reduction with Ant Colony Algorithm

Abstract

The ability of the Distributed Generation (DG) to solve problems such as power system deregulation and power demand problems appropriate to its purpose, which is to inject electricity in a distributed manner at a point close to the load, causes the distributed generation to become the latest trend in electricity generation technology. Proper position of distributed generation is necessary in order to achieved maximum benefit from DG, which could be due to an incorrect allocation of DG sources to the power network would not only result in increased power losses, but could also jeopardize the operation of the system. This paper introduces an ACO-algorithm for optimal location of DGs using a real network in one of a rural area of Malaysia. The method is used to determine the effectiveness of DG by comparing the losses of power and the improvement of the voltage profile. As for the confirmation to the ACO method, another method known as brute force method is use to compare the data gain as validation purposes.

Optimal Allocation and Size of Renewable Energy Sources as Distributed Generations Using Shark Optimization Algorithm in Radial Distribution Systems

“…Most of these works used some optimization techniques to solve the optimal location and size issues for DGs. Genetic Algorithm [17], Particle Swarm Optimization [18,19], Modified Bacterial Foraging Optimization [20], Bat Approach [21], Invasive Weed Optimization [22], Water Cycle Algorithm [23], Ant Colony Algorithm [24,25], Modified Teaching-Learningbased Optimization Algorithm [26], Hybrid Big Bang-Big Crunch Approach [27], Gray Wolf Optimization [28], Cuckoo Search Algorithm [29][30][31], Heuristic Methods [32], Chaotic Symbiotic Organisms Search Algorithm [33], and Marine Predators Optimizer [34] were introduced to deal with the DG placement process. Using three typical radial systems, IEEE 33 [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51], 69 [52][53][54][55][56][57][58][59][60][61], and 85 …”