Optimization the stochastic optimal reactive power dispatch with renewable energy resources using a modified dandelion algorithm.

ABSTRACT: Improvement performance of transmission systems is crucial task that can be boosted via optimal reactive power dispatch (ORPD). However, the continuous variations of load demand and the power produced by the renewable energy sources (RERs) increases the complicities of solving the stochastic optimal reactive power dispatch (SORPD) solution. In this regard, a modified Dandelion Optimizer (MDO) algorithm is introduced to optimize the SORPD solution with taking into consideration the stochastic fluctuations or the random variations of the load demand and the power produced by RERs. The suggested MDO depends upon developing the searching exploration and exploitation abilities by integration of three methodologies involving the Quasi-oppositional-based-learning (QOBL), the Weibull flight motion

SUBMITTER: Agouzoul N 

PROVIDER: S-EPMC12273990 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature