Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Development of Optimal Electricity Management Systems to Minimize Resources and Losses using Particle Swarm Optimization Techniques: A Case Study for UDUS

Domaine:

environment and energy

Type de record:

paper
Créateur:
A.
Éditeur:
Ahm
Hôte:
Hybrid energy systems (HESs), have played an important role as clean and efficient source of electricity generation. HESs are often formulated as an optimization problem which is solved mostly using metaheuristics techniques. The conventional objective function is based on levelized cost of energy (LCOE), the lowest loss of power supply probability (LPSP), and the maximum renewable factor (REF) as indices. This paper proposed an enhanced objective function based on additional index known as Lost Load Dump Load Index (LLDLI), which helps in finding optimal solution to HES deployment. Usmanu Danfodiyo University Sokoto (UDUS), Nigeria is used as case study, Particle swamp optimization (PSO)is used to solve the optimization problem in MATLAB/Simulink for its early convergence. With the proposed method, an optimal solution for the allocation of HES resources is achieved with minimum LCOE, LPSP, and LLDL indices that are equal to 1.21$/kWh and 0.04%, and 0.05%respectively against conventional PSO of The minimum parameters come out to be 1.3$/kWh for LCOE, 0.06% for LPSP, 0.09I.

Visit

doi.org

Languages

Fulfulde, NigerianHausa

Similaires

Optimal Siting and Sizing of Distributed Generators for Voltage Stability Enhancement Using a Particle Swarm Optimization FrameworkOptimal Design of Grid-Connected Solar Photovoltaic System Using Selective Particle Swarm OptimizationParameters Optimization of Deep Learning Models using Particle Swarm OptimizationOptimal Reconfiguration of Radial Distribution Network for Loss Minimization Using Hybrid Genetic Algorithm-Particle Swarm Optimization AlgorithmExtreme Learning Machine Weight Optimization using Particle Swarm Optimization to Identify Sugar Cane DiseasePREDICTION OF GROUNDWATER SALINIZATION USING PARTICLE SWARM OPTIMIZATION FOR NEURAL NETWORK TRAINING

Optimal Siting and Sizing of Distributed Generators for Voltage Stability Enhancement Using a Particle Swarm Optimization Framework

International audience This study investigated the enhancement of voltage stability i

Optimal Design of Grid-Connected Solar Photovoltaic System Using Selective Particle Swarm Optimization

The electricity distribution network in Ethiopia has the radial nature of network configuration. The

Parameters Optimization of Deep Learning Models using Particle Swarm Optimization

Deep learning has been successfully applied in several fields such as machine translation, manufactu

Optimal Reconfiguration of Radial Distribution Network for Loss Minimization Using Hybrid Genetic Algorithm-Particle Swarm Optimization Algorithm

Aim: The aim of this research is to minimize power losses and improve the voltage profile of the Ado

Extreme Learning Machine Weight Optimization using Particle Swarm Optimization to Identify Sugar Cane Disease

Sugar cane disease is a major factor in reducing sugar cane yields. The low intensity of experts to

PREDICTION OF GROUNDWATER SALINIZATION USING PARTICLE SWARM OPTIMIZATION FOR NEURAL NETWORK TRAINING

Monitoring groundwater quality is a costly and time-c