Journal ArticleDOI
Transient stability constrained optimal power flow using particle swarm optimisation
TLDR
In this article, a particle swarm optimisation (PSO) technique is proposed for the transient-stability constrained optimal power flow (TSCOPF) problem, which is formulated as an extended OPF with additional rotor angle inequality constraints.Abstract:
A novel approach based on the particle swarm optimisation (PSO) technique is proposed for the transient-stability constrained optimal power flow (TSCOPF) problem. Optimal power flow (OPF) with transient-stability constraints considered is formulated as an extended OPF with additional rotor angle inequality constraints. For this nonlinear optimisation problem, the objective function is defined as minimising the total fuel cost of the system. The proposed PSO-based approach is demonstrated and compared with conventional OPF as well as a genetic algorithm based counterpart on the IEEE 30-bus system. Furthermore, the effectiveness of the PSO-based TSCOPF in handling multiple contingencies is illustrated using the New England 39-bus system. Test results show that the proposed approach is capable of obtaining higher quality solutions efficiently in the TSCOPF problem.read more
Citations
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Journal ArticleDOI
Optimal power flow: a bibliographic survey I
TL;DR: Optimal power flow (OPF) has become one of the most important and widely studied nonlinear optimization problems as mentioned in this paper, and there is an extremely wide variety of OPF formulations and solution methods.
Journal ArticleDOI
Optimal power flow: A bibliographic survey II non-deterministic and hybrid methods
TL;DR: Optimal power flow (OPF) has become one of the most important and widely studied nonlinear optimization problems as discussed by the authors, and there is an extremely wide variety of OPF formulations and solution methods.
Journal ArticleDOI
Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications
TL;DR: A new hybrid particle swarm optimization that incorporates a wavelet-theory-based mutation operation is proposed that significantly outperforms the existing methods in terms of convergence speed, solution quality, and solution stability.
Journal ArticleDOI
Improved Hybrid Particle Swarm Optimized Wavelet Neural Network for Modeling the Development of Fluid Dispensing for Electronic Packaging
TL;DR: An improved hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for modeling the development of fluid dispensing for electronic packaging (MFD-EP) is presented, which incorporates a wavelet-theory-based mutation operation.
Journal ArticleDOI
A review of optimal power flow studies applied to smart grids and microgrids
TL;DR: In this article, the main OPF approaches are compared in terms of their objective functions, constraints, and methodologies, and some basic challenges arising from the new OPF methodologies in smart grids are addressed.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
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TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
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A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
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