Proceedings ArticleDOI
Cluster Based Congestion Management in Deregulated Electricity Market Using PSO
TLDR
The aim of the proposed work is to minimize deviations from transaction schedules and hence the congestion cost, using the Cluster based congestion management method.Abstract:
In this Paper, a Cluster based congestion management has been presented. The Paper is concerned with the Real and Reactive power rescheduling problem in a deregulated market environment. The aim of the proposed work is to minimize deviations from transaction schedules and hence the congestion cost. The TCSC maximizes the power transfer capability between a specific power seller and a power buyer in a network. The TCSC is installed in the most congested lines and analyzed. The method is formulated as a stochastic optimization problem and is solved by Particle Swarm Optimization. The algorithm is illustrated using New England 39-bus system.read more
Citations
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Journal ArticleDOI
Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization
S. Dutta,Shiv P. Singh +1 more
TL;DR: An algorithm based on particle swarm optimization (PSO) which minimizes the deviations of rescheduled values of generator power outputs from scheduled levels and handles the binding constraints by a technique different from the traditional penalty function method is proposed.
Journal ArticleDOI
Optimal congestion management in an electricity market using particle swarm optimization with time-varying acceleration coefficients
TL;DR: Test results on IEEE 30-bus and 118-bus systems indicate that the PSO-TVAC approach could provide a lower rescheduling cost solution compared to classical particle swarm optimization and particle Swarm optimization with time-varying inertia weight.
Proceedings ArticleDOI
Congestion management by generator rescheduling using Artificial Bee Colony optimization Technique
Subhasish Deb,Arup Kumar Goswami +1 more
TL;DR: The proposed ABC algorithm is a new metaheuristic approach inspired by intelligent foraging behavior of honeybee swarm for congestion management problem and is applied on IEEE 39 Bus New England test system.
Journal ArticleDOI
Application of Differential Evolution for Congestion Management in Power System
Sujatha Balaraman,N. Kamaraj +1 more
TL;DR: The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.
Proceedings ArticleDOI
Mitigation of congestion by generator rescheduling using Particle Swarm Optimization
Subhasish Deb,Arup Kumar Goswami +1 more
TL;DR: In this article, a generator rescheduling algorithm is proposed to mitigate transmission congestion in a deregulated electricity market, which is done in an Optimal Power Flow (OPF) framework to minimize the overall congestion relief cost.
References
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Proceedings ArticleDOI
Particle swarm optimization: surfing the waves
Ender Özcan,Chilukuri K. Mohan +1 more
TL;DR: This paper takes the next step, generalizing to obtain closed form equations for trajectories of particles in a multi-dimensional search space.
Journal ArticleDOI
A zonal congestion management approach using real and reactive power rescheduling
TL;DR: In this article, a new zonal/cluster-based congestion management approach has been proposed, where the zones have been determined based on lines real and reactive power flow sensitivity indexes also called as real/reactive transmission congestion distribution factors, and generators in the most sensitive zones, with strongest and nonuniform distribution of sensitivity indexes, are identified for rescheduling their real power output for congestion management.
Proceedings ArticleDOI
EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems
Vladimiro Miranda,N. Fonseca +1 more
TL;DR: The fundamentals of the method are described, and an application to the problem of loss minimization and voltage control is presented, with very good results.
Proceedings ArticleDOI
Allocation of TCSC devices to optimize total transmission capacity in a competitive power market
Wang Feng,G.B. Shrestha +1 more
TL;DR: In this paper, a genetic algorithm is used as the optimization tool to determine the location as well as the parameters of TCSC simultaneously, which can help increase power transfer capacity in heavily loaded networks because of its capability to control power flow flexibly.
Proceedings ArticleDOI
Congestion clusters-based markets for transmission management
Chien-Ning Yu,Marija Ilic +1 more
TL;DR: In this article, the authors propose a method for effective grouping of system users according to their impact on the transmission constraints of interest into congestion clusters, which can be used for facilitating either a spot transmission management market, or an entirely decentralized transmission market.
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