On‐line parameter identification of power plant characteristics based on phasor measurement unit recorded data using differential evolution and bat inspired algorithm

Rashidi, Farzan; Abiri, Ebrahim; Niknam, Taher; Salehi, Mohammad Reza

doi:10.1049/iet-smt.2014.0022

Cited by 16 publications

(5 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the clustering centers are random, the proposed CSD usually cannot be obtained by once operation of the program. Thereby, a self-adaptive differential evolution method (SADE) [25][26][27] is proposed to improve the CSD through optimization of the initial clustering centers.…”

Section: Self-adaptive Differential Evolution Methodsmentioning

confidence: 99%

Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

Wu¹,

Liu²,

Qin³

et al. 2017

J. vibroeng.

View full text Add to dashboard Cite

A novel clustering stabilization diagram combined with self adaptive differential evolution algorithm is proposed to identify the modal parameters of civil engineering structures. Compared with the traditional stabilization diagram, the clustering diagram has drawn more attention because it can distinguish physical and spurious modes due to its automatic performance. In this paper, a self adaptive differential evolution algorithm is proposed to optimize the initial clustering centers so as to improve the clustering stabilization diagram. Moreover, this paper presents a new idea that the modal assurance criterion (MAC) composed of mode shapes is selected as the-axis to replace the model orders or damping ratios in existing stabilization diagrams. The results of a benchmark test of bridge Z24 and the numerical simulation of a continuous beam and a cable-stayed bridge demonstrate the advantages of the proposed approaches and the reliability of detecting the modal parameters.

show abstract

Section: Self-adaptive Differential Evolution Methodsmentioning

confidence: 99%

Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

Wu¹,

Liu²,

Qin³

et al. 2017

J. vibroeng.

View full text Add to dashboard Cite

show abstract

“…The DHJS algorithm has proven to be a widely-used solution for resolving complex engineering and scheduling problems, with the goal of maximizing efficiency and costeffectiveness. In this research, we present a novel method that accurately enhances resource availability in the context of parallel processing demands within cloud environments [20].…”

Section: Major Contributionsmentioning

confidence: 99%

MTD-DHJS: Makespan-Optimized Task Scheduling Algorithm for Cloud Computing With Dynamic Computational Time Prediction

Banerjee,

Roy,

Sinha

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The results achieved with BA were proved to be better when compared to PSO and Intelligent Water Droplet (IWD) algorithm [41]. Rashidi et al have combined BA with Differential Evolution (DE) algorithm to formulate a hybrid algorithm to optimize the estimation of power system model parameters [42]. Furthermore Niknam et al have addressed the unit commitment issue and concentrated their research in formulating a self adaptive BA.…”

Section: Introductionmentioning

confidence: 99%

Bat Algorithm for Congestion Alleviation in Power System Network

Paul¹,

Kumar

Dalapati³

2021

Technol Econ Smart Grids Sustain Energy

View full text Add to dashboard Cite

On‐line parameter identification of power plant characteristics based on phasor measurement unit recorded data using differential evolution and bat inspired algorithm

Cited by 16 publications

References 48 publications

Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

MTD-DHJS: Makespan-Optimized Task Scheduling Algorithm for Cloud Computing With Dynamic Computational Time Prediction

Bat Algorithm for Congestion Alleviation in Power System Network

Contact Info

Product

Resources

About