Resources Policy, Journal Year: 2024, Volume and Issue: 94, P. 105104 - 105104
Published: June 4, 2024
Language: Английский
Resources Policy, Journal Year: 2024, Volume and Issue: 94, P. 105104 - 105104
Published: June 4, 2024
Language: Английский
PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0319422 - e0319422
Published: April 2, 2025
Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into distribution system to address issues related generation (DG) allocation. The key implications integrating RDGs include improvement voltage profiles minimization power losses. Various optimization techniques, namely Salp Swarm Algorithm (SSA), Marine Predictor (MPA), Grey Wolf Optimizer (GWO), Improved (IGWO), Seagull Optimization (SOA), have been applied achieve optimal allocation sizing in radial systems (RDS). present paper is structured two phases. In initial phase, Loss Sensitivity Factor (LSF) employed identify most suitable nodes for RDGs. second within selected candidate from first location capacity are determined. Additionally, a comprehensive comparison proposed methods conducted select effective solutions units efficacy utilized techniques validated through testing distinct networks, IEEE 33 69 buses RDS MATLAB, with attainments compared against other techniques. Moreover, larger 118- bus considered order enhance its quality indices. real case study Egypt 15 evaluated considering results show enhancement profile decreasing losses tested DG superiority MPA SSA algorithms.
Language: Английский
Citations
1Resources Policy, Journal Year: 2024, Volume and Issue: 94, P. 105104 - 105104
Published: June 4, 2024
Language: Английский
Citations
3