HybridBOA‐GWO‐PSOalgorithm for mitigation of congestion by optimal reactive power management

Abstract

The generation of power with load optimization, particularly in the current deregulated electricity market conditions, is a very important process for improved planning and operation of the grid. In addition, it is very important for the system not to experience problems due to congestion, have tensile stability, and protection to increase the share of electricity from renewable sources with the current supply system. This article presents load balancing with the butterfly optimization algorithm (BOA) in a hybridized form to minimize and maximize loads when used in pool and hybrid markets. The methods have been designed to prevent the drawbacks of BOA and generate a better trade-off between exploration and exploitation abilities by hybridizing it with particle swarm optimization (PSO) and gray wolf optimizer (GWO). Empirical research on other algorithms shows that proposed hybrid BOA-GWO-PSO algorithm performs better and shows potential in diverse problems. These studies give it a significant advantage over BOA in general, and when it is employed to solve complex optimization problems validated on benchmark IEEE 30 bus system. A comparative analysis has been conducted to validate the potency of the hybrid BOA-GWO-PSO approach with some conventional meta-heuristic algorithms.Analysis of results by mathematical validation on 23 benchmark functions and application in congestion management by optimal reactive power management (RPM) reveal that the proposed technique has the potent to solve real world optimization problems and is competitive with recent methods reported in state-ofart literature.

Research on automatic matching of online mathematics courses and design of teaching activities based on multiobjective optimization algorithm

“…The value of RMP allows for balancing between exploration and exploitation of the search space. When RMP ( Badi, Mahapatra & Raj, 2023 ) is close to 1, students will always receive knowledge transfer from individuals with the same attribute, which can help scan critical areas of the search space but increase the risk of falling into local optima. Conversely, when rmp is lower than 1, communication between individuals from different cultures can aid in escaping local optima.…”

An enhanced arithmetic optimization algorithm for optimal control of reactive power

“…Initiate two random number g2 and g3 in the range between 0 to 1 using gamma distribution Modify the solution by executing logarithmic operator using Equation (23).…”

“…Shaheen et al 22 proposed a hybrid Grey Wolf Optimization and Particle Swarm Optimization (GWO‐PSO) for optimal reactive power flow within the power network to reduce losses and voltage deviation. Saurav et al 23 proposed a hybrid BOA‐GWO‐PSO algorithm for improving congestion through ORPD. Saurav et al 24 present a hybrid oppositional‐based marine predators' algorithm (OMPA) and Harris Hawks' optimization (HHO) for reactive power management.…”

Convolutional neural networks optimized with an improved butterfly optimization algorithm for fault diagnosis

“…BOA [12] DA [6] ALO [5] GWO [8] MFO [9] IBOA under different benchmark functions. The algorithms selected in the experiment included PILBOA [13] , SCLBOA [15] , GPBOA [16] ,…”

“…Badi et al [16] introduced PSO and GWO into BOA, which improved the convergence accuracy of the algorithm. Arora [17] used a fixed switching probability to jointly optimize BOA and artificial bee colony algorithm (ABC) algorithms, which improved the search accuracy.…”