A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties

• Main Authors: Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir
• Format: Article
• Language: English
• Published: Elsevier Inc. 2024
• Subjects: QA75 Electronic computers. Computer science; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/40103/1/A%20new%20optimisation%20framework%20based%20on%20Monte%20Carlo%20embedded%20hybrid%20variant%20mean%E2%80%93variance%20mapping%20considering%20uncertainties.pdf; http://umpir.ump.edu.my/id/eprint/40103/; https://doi.org/10.1016/j.dajour.2023.100368

This study proposes a new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping (MVMO-SH) optimisation​ for planning Photovoltaic Distributed Generation (PVDG) in the urban Radial Distribution Network (RDN). The Active Power Loss (APL) index was calculated conside...