PSO based OPF technique ensuring small signal stability

Anumod, D. M.; Raj, M. Devesh

doi:10.1109/aicera.2014.6908284

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…These elements are real and imaginary parts of the eigenvalues and participation factors between various eigenvalues and state variables. 2,6,10,14,18,22,26,30,34]…”

Section: Discussionmentioning

confidence: 99%

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Polynomial Approximation of Power System Eigenvalues for Fast Small Signal Stability Analysis

Khodaei¹

2022

Preprint

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<p>In power system dynamic analysis, computation of eigenvalues of state equations for various active dispatched powers is important. This concept provides a better understanding of the system dynamic behavior. In this paper, an approximate equation extraction technique is proposed for fast computation of real-part of the most critical eigenvalue of New England 39-bus power system. Simulation by using MATLAB PSAT toolbox is carried out as a source of the initial data for finding a proper approximate function and also its verification. As an application example, the obtained polynomial approximate function has been applied to small signal stability constrained optimal power flow by using GAMS optimization package. The obtained polynomial function can be used with various optimization criteria in the valid interval of the approximation. Also this polynomial function can be re-used when generation cost functions are changed, without need for a new dynamic analysis. All of the dynamic analyses by PSAT toolbox are performed by using automatic intermediate codes cooperating with functions and variables of the PSAT toolbox and handy registration of numbers is avoided. </p>

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“…These elements are real and imaginary parts of the eigenvalues and participation factors between various eigenvalues and state variables. 2,6,10,14,18,22,26,30,34]…”

Section: Discussionmentioning

confidence: 99%

“…In [3] and [4], methods of SLP and SOPF have been used respectively. Also [5], [6] and [7] have employed methods of SDP, PSO and SQP, respectively. In [8], the stability constraint has been applied on the most critical eigenvalue whose identities may differ for various simulation samples.…”

Section: Introductionmentioning

confidence: 99%

Polynomial Approximation of Power System Eigenvalues for Fast Small Signal Stability Analysis

Khodaei¹

2022

Preprint

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“…For SSS studies in power systems, non-linear control analysis such as Lyapunov can be used. However, in most research works in the area, eigenvalue analysis is usually considered for SSS (for instance, [1,2,[5][6][7][8][9][10][11][12]).…”

Section: Small Signal Stability Assessmentmentioning

confidence: 99%

“…A real-time method is suggested in [5], to increase the SSS by adjusting power flow algorithm and adding an SSS index into the OPF model. The OPF with the SSS constraint is solved by using particle swarm optimisation algorithm in [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal re‐dispatch of generating units ensuring small signal stability

Adeli

Rabiee

Boroujeni

2020

IET Generation, Transmission & Distribution

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“…Anumod, D.M. et al [36] describes optimal power flow based on particle swarm optimization in which the power transmission loss function is used as the problem objective. Although most of optimal power flow problems involve the total production cost of the entire power system, in some cases some different objective may be chosen.…”

Section: F Particle Swarm Optimization (Pso)mentioning

confidence: 99%

A Review of Artificial Intelligence Based Optimization Techniques for Optimal Power Flow

2016

IJAERD

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This paper presents a review of different Artificial Intelligence (AI) methods which are one of the latest computational intelligent techniques to solve optimal power flow (OPF) problems. OPF is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming (LP), Newton Raphson (NR) and Non-Linear Programming were previously offered to tackle the complexity of the OPF. However, with emergence of AI methods, many novel techniques such as Artificial neural network (ANN), Fuzzy Logic (FL), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Algorithm (BFA), and Artificial Bee Colony (ABC) have also received great attention. This paper gives detailed discussion of AI based optimization techniques to solve OPF problem which are more effective.

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PSO based OPF technique ensuring small signal stability

Cited by 4 publications

References 21 publications

Polynomial Approximation of Power System Eigenvalues for Fast Small Signal Stability Analysis

Polynomial Approximation of Power System Eigenvalues for Fast Small Signal Stability Analysis

Optimal re‐dispatch of generating units ensuring small signal stability

A Review of Artificial Intelligence Based Optimization Techniques for Optimal Power Flow

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