An improved hybrid approach for the simultaneous allocation of distributed generators and time varying loads in distribution systems

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Ali Ahmed - , University of Engineering and Technology, Taxila (Author)
  • Muhammad Faisal Nadeem - , University of Engineering and Technology, Taxila (Author)
  • Arooj Tariq Kiani - , Air University, Islamabad (Author)
  • Nasim Ullah - , Taif University (Author)
  • Muhammad Adnan Khan - , Gachon University (Author)
  • Amir Mosavi - , Slovak University of Technology, Óbuda University, TUD Dresden University of Technology (Author)

Abstract

Distributed Generation (DG) studies are generally conducted considering a single type of DG units integrated with the Distribution System (DS). However, these studies may not evaluate optimum benefits offered by the DG integration. This paper presents a novel framework for individual and simultaneous allocation of different types of DG units in DS while considering varying load demand and probabilistic generation of DG units. A Salp Swarm Algorithm (SSA) and Particle Swarm Optimization (PSO) based new hybrid method that utilizes a single controlling parameter is proposed for simultaneous allocation of DG units, aiming to minimize a multi-objective index. The strength of the proposed SSA-PSO hybrid approach is validated on seventeen benchmark functions and the performance of the novel framework for optimal allocation of DG units is validated through implementation on the 69-bus system. The results demonstrate that the proposed hybrid approach performs better as compared to other meta-heuristics techniques. Moreover, simultaneous allocation significantly reduces the multi-objective index as compared to individual DG units’ integration.

Details

Original languageEnglish
Pages (from-to)1549-1560
Number of pages12
JournalEnergy reports
Volume9
Publication statusPublished - Dec 2023
Peer-reviewedYes

Keywords

ASJC Scopus subject areas

Keywords

  • Distributed generation, Metaheuristics, Multi-objective index, Optimal allocation