Publication: A Hybrid Multi-objective Integrated JAYA-Evolutionary Programming (MOIJEP) Algorithm for Under Voltage Load Shedding (UVLS) Scheme in Bulk Power System
Date
2024
Authors
Shukor S.F.A.
Musirin I.
Hamid Z.A.
Senthil Kumar A.V.
Mansor M.H.
Salimin R.H.
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
Progressing demand can lead to voltage decay in a power system which causes under-voltage phenomenon. Load shedding is a reliable last option to secure a power system from possible voltage collapse occurrence when unintended disturbance occurs. Under Voltage Load Shedding (UVLS) is one of the suitable methods to overcome further unsecure operation. This will require a reliable optimization technique to identify the most suitable locations and sizing for UVLS scheme. This paper presents a hybrid multi-objective integrated jaya-evolutionary programming (MOIJEP) algorithm for under voltage load shedding (UVLS) scheme in bulk power system. MOIJEP integrates the features in the original Jaya algorithm into the conventional Evolutionary Programming (EP). A weighted sum multi-objective which considers voltage stability index, loss and minimum voltage in the system is formulated in this study, implemented for multi-load shedding scheme. Results obtained using the proposed MOIJEP are superior to the benchmarked technique, i.e., MOIJEP when validated on the IEEE 57-Bus Reliability Test System (RTS). ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Description
Keywords
Computer programming , Electric load shedding , Electric power plant loads , Evolutionary algorithms , Power quality , Bulk power systems , Evolutionary and jaya algorithm , Evolutionary programming algorithms , Load shedding scheme , Load-shedding , Multi objective , Multi-objectives optimization , Power , Under-voltage load shedding , Undervoltage , Multiobjective optimization