Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

• Published in: SN applied sciences Vol. 3; no. 2; p. 248
• Main Authors: Ogunsina, Adeseye Amos, Petinrin, Moses Omolayo, Petinrin, Olutomilayo Olayemi, Offornedo, Emeka Nelson, Petinrin, Joseph Olawole, Asaolu, Gideon Olusola
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2021; Springer Nature B.V
• Subjects: 3. Engineering (general); Algorithms; Alternative energy sources; Ant colony optimization; Applied and Technical Physics; Chemistry/Food Science; Distributed generation; Earth Sciences; Electric potential; Electric power distribution; Electric power loss; Energy resources; Engineering; Environment; Genetic algorithms; Linear programming; Materials Science; Optimization algorithms; Pheromones; Renewable resources; Research Article; Sizing; Voltage; Renewable energy; Power flow; Ant colony optimization (ACO); Distributed generation (DG); Voltage quality
• ISSN: 2523-3963; 2523-3971; 2523-3971
• DOI: 10.1007/s42452-021-04226-y

A system of power generation whereby the generating equipment is located close to the point of usage, thereby reducing losses and operation cost is called distributed generation (DG). However, it is imperative that DGs are sited such that the quality of power delivered is optimized and the total real power loss within the system minimized. This paper proposes an approach for optimum sizing and siting of DGs sizing in a power distribution system using Ant Colony Optimization (ACO) algorithm. To validate the algorithm the IEEE 30 bus standard test system was employed. A 92% decrease in real power loss within the system relative to the value before the connection of DGs was observed, while the minimum bus voltage increased from 0.656 per unit to 0.965 per unit. The results obtained from ACO are further verified by creating an ETAP model of the IEEE 30 bus system and simulating the impact of DG on the system. A significant reduction in total real power losses within the system and improvement in voltage profile was observed when the DGs are placed at the ACO derived sites relative to at other locations. Therefore, Ant Colony Algorithm can be used in deriving the optimum sites and sizes of DGs in a power distribution system.