Rescheduling‐based congestion management by metaheuristic algorithm: Hybridizing lion and moth search models

Srivastava, Jyoti; Yadav, Naresh Kumar

doi:10.1002/jnm.2952

Cited by 7 publications

(3 citation statements)

References 42 publications

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“…In [14] an OPF based approach considering the GR technique has been developed to control the transmission of excess power flowing through the lines. In another research, Srivastava and Yadav proposed a hybrid lion and moth search technique for the optimal GR of real power to alleviate congestion while maintaining the stability limits [15]. In [16], Yesuratnam and Thukaram also used the GR technique for CM.…”

Section: A Literature Surveymentioning

confidence: 99%

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A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

Paul¹,

Sinha

Bouteraa

et al. 2023

IEEE Access

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This research manuscript proposes an Improved Manta Ray Foraging Optimization (IMRFO) algorithm for the power system congestion cost problem. The goal of the proposed Congestion Management (CM) strategy is twofold: firstly, the Generator Sensitivity Factors (GSF) is determined to select and involve the most influential power system generators that will reschedule their real power to alleviate the excess power flow in congested transmission lines. Secondly, the IMRFO has been developed and applied to attain the minimum possible congestion cost. The IMRFO has been formulated with the inclusion of correction factors in the exploration and exploitation phases to improve the coordination between these phases. The effectiveness of IMRFO has been measured considering its effective performance on the 23 conventional benchmark functions. 39 bus New England and IEEE-118 bus test system has been utilized to authenticate the effectiveness of the CM approach with the application of IMRFO. The outcomes highlight that the congestion cost achieved with IMRFO has been reduced by, of 16.08%, 13.73%, 11.78%, and 4.48 % for the 39-bus system and 14.84%, 12.97%, 9.63%, and 6.85% for 118 bus system when compared to the Bacteria Forge Optimization (BFO), Grey Wolf Optimization (GWO), Sine-Cosine Algorithm (SCA), and Original MRFO. The results gained with the implementation of IMRFO on the CM problem portrays appreciable minimization in the congestion cost, enhancement in the system voltage and losses, generates better convergence profile and computational time when contrasted with the recent optimization methods.INDEX TERMS Manta ray forge optimization, meta-heuristic technique, optimal power flow, optimization, power rescheduling, sensitivity analysis.

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Section: A Literature Surveymentioning

confidence: 99%

“…The line L(14-34) joining the buses 14-34 has been tripped. This tripping of the line L(14-34) has resulted congestion in the line L (15)(16) with the increase in power flow to 628.2 MW (Line limit 500MW).…”

Section: A 39-bus New England Systemmentioning

confidence: 99%

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

Paul¹,

Sinha

Bouteraa

et al. 2023

IEEE Access

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“…Hence, eq. ( 1) devises the complete issue which is considered as a constrained minimization function [14].…”

Section: Congestion Management Problem Formulationmentioning

confidence: 99%

A Novel World Horse Optimizer Algorithm for Rescheduling based Congestion Management

2021

JCMPS

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In a power system, Congestion Management is considered a demanding task because of maximizing the complexities of the system in a deregulated environment. The congestion reasons severe damage to modules of the power system if outages lead to take place additional regularly. Therefore, Congestion Management is a complicated task for an Independent System Operator (ISO) in the present case of the power system. This paper presents a proposal for a new optimization-based Congestion Management approach with a developed soft computing model. In this work, a novel hybrid approach is developed that clearly optimizes the power of the augmented generator with a bus system. Thus, the congestion is managed with a reduced cost of rescheduling. The adopted optimization approach is called Wild Horse Optimizer (WHO). Then, the simulation is performed on two test bus systems such as IEEE 14 as well as 30 bus systems. The adopted approach performance is evaluated with conventional techniques regarding the cost analysis.

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Navigating Power System Congestion: An In-Depth Review of Traditional and Artificial Intelligence-Driven Approaches

Hamza,

Ahmad,

Ahmad

et al. 2023

2023 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)

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Rescheduling‐based congestion management by metaheuristic algorithm: Hybridizing lion and moth search models

Cited by 7 publications

References 42 publications

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

A Novel World Horse Optimizer Algorithm for Rescheduling based Congestion Management

Navigating Power System Congestion: An In-Depth Review of Traditional and Artificial Intelligence-Driven Approaches

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