Optimal Siting of FACTS Controller Using Moth Flame Optimization Technique

Kumari, Shweta; Kar, Manoj Kumar; Kumar, Lalit; Kumar, Sanjay

doi:10.1007/978-981-19-0193-5_7

Cited by 5 publications

(1 citation statement)

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“…Since the IDE method is a modified version of DE, some variants of DE are chosen for comparison. As DE (Abou El Elaa et al, 2011), MFO (KAR et al, 2020;Kumar et al, 2021;Kumari et al, 2022), BSOA (Jordehi, 2015), PSO (Bhattacharyya & Kumar, 2016) T A B L E 3 WSRT results on unimodal and multimodal functions denoting the equivalency (≈), superiority (+), or inferiority (À) method when compared with the proposed method 96, 99, 133, 152, 158, 227, 268, 283 143, 145, 169, 210, 217, 219 parameters f and Cr set to 0.5 and 0.6, respectively. The MFO and BSOA control parameters are set in accordance with the parameters of the base papers.…”

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confidence: 99%

Statistical analysis based reactive power optimization using improved differential evolutionary algorithm

2022

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This study presents a novel improved differential evolutionary (IDE) algorithm for optimizing reactive power management (RPM) problems. The effectiveness of IDE algorithm is tested on different unimodal and multimodal benchmark functions. The objective function of the RPM is considered as the minimization of active power losses. Initially, the power flow analysis approach is employed to detect the optimal position of flexible AC transmission system (FACTS) devices. The proposed method is used to determine the optimal value of control variables such as generator's reactive power generation, transformer tap settings, and reactive power sources. Furthermore, the efficacy of the IDE approach is compared with other promising optimization methods such as variants of differential evolution algorithm, moth flame optimization (MFO), brainstorm-based optimization algorithm (BSOA), and particle swarm optimization (PSO) on various IEEE standard test bus (i.e., IEEE-30, -57, -118, and -300) systems with active and reactive loading incorporating FACTS devices. A Static VAR compensator (SVC) for shunt compensation and a thyristor-controlled series compensator (TCSC) for series compensation were used as FACTS devices.The proposed IDE method significantly reduces the active power loss, that is, 55.65% in IEEE 30, 39.68% in IEEE 57, 16.32% in IEEE 118, and 8.56% in IEEE 300 bus system at nominal loading. Finally, the statistical analysis such as Wilcoxon signed-rank test (WSRT) and ANOVA test were thoroughly analysed to demonstrate the firmness and accuracy of the proposed technique.active power loss, FACTS devices, improved differential evolution, load flow analysis, optimal placement, statistical analysisExisting power transmission lines operating under extreme stress and transmitting power close to their thermal limits which causes grid disruptions and violations of different operating constraints. In this scenario, reactive power management becomes a challenging task for power

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