A combined framework for service identification and congestion management

Fu, Jing; Lamont, J.W.

doi:10.1109/59.910781

Cited by 39 publications

(12 citation statements)

References 9 publications

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“…Relieving congestions caused by voltage instability and thermal overloads is taken in [15]. This also uses OPF which is solved by standard solvers.…”

Section: Introductionmentioning

confidence: 99%

Black Hole Algorithm Implemented for Congestion Management in a Competitive Power Market

Ramachandran¹,

Arun²

2016

IJCA

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Transmission congestion is the major challenge in the operation of competitive power market. Sufficient transmission corridor is necessary for realization of power transaction. This paper proposes an efficient approach for transmission congestion management using the Black Hole Algorithm (BHA). Congestion is relieved by rescheduling of real power from the market clearing schedule. BHA is a recently introduced nature inspired algorithm with less number of parameters. The algorithm is easy for implementation, takes less number of iterations and tuning for a particular application. The strength of the algorithm is validated by comparing its performance with that of Particle Swarm Optimization (PSO) and Big Bang Big Crunch (BBBC) algorithms available in the literature. Modified IEEE-30 and Modified IEEE-57 bus systems are taken for the simulation purpose. General TermsCompetitive power market, black hole algorithm.

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“…Relieving congestions caused by voltage instability and thermal overloads is taken in [15]. This also uses OPF which is solved by standard solvers.…”

Section: Introductionmentioning

confidence: 99%

Black Hole Algorithm Implemented for Congestion Management in a Competitive Power Market

Ramachandran¹,

Arun²

2016

IJCA

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“…An OPF-based approach that minimizes cost of congestion and service costs is proposed in [2]. In [3], OPF based technique has been proposed for relieving congestion due to voltage instability and thermal overloads.…”

Section: Introductionmentioning

confidence: 99%

Transmission Congestion Management in Restructured Power System using Firefly Algorithm

AhamedJeelaniBasha¹,

Anitha²

2014

IJCA

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Transmission congestion management is one of the critical and important tasks of the system operator. Transmission line congestion is considered to be more important as it may initiate the cascading outages which forces the system to collapse. This paper presents a transmission congestion management (CM) algorithm by optimal rescheduling of active powers of generators using firefly (FF) algorithm. All the generators in the system need not take part in CM. Generator sensitivity to the congested line and the cost of generation are considered while rescheduling the generators to alleviate congestion. In this paper an efficient FF algorithm is used for solving CM problem. The proposed method has been tested on IEEE 30 bus system and the results of various case studies have been compared with that of RCGA & SA methods. Results prove that FF algorithm is indeed capable of obtaining higher quality solutions for the CM problem.

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“…Both WFs are correlated with a correlation coefficient 0.9 and a power factor 0.9 lag. Besides, the involved parameters are set as follows: w V =10 6 , w P =10 6 , Iter max =200 and Lim max =100. Firstly, the original outputs of the generators are calculated by minimizing the electricity purchase cost without constraints (9)- (11).…”

Section: Modified Ieee 30-bus Case Studymentioning

confidence: 99%

“…Another OPF-based scheme which aims to minimize both congestion and service costs is presented in [6]. Various kinds of traditional congestion management models are essentially the OPF problems associated with security constraints.…”

Section: Introductionmentioning

confidence: 99%

A Congestion Management Approach Using Probabilistic Power Flow Considering Direct Electricity Purchase

Wang¹,

Jiang²

2015

Journal of Electrical Engineering and Technology

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-In a deregulated electricity market, congestion of the transmission lines is a major problem the independent system operator (ISO) would face. Rescheduling of generators is one of the most practiced techniques to alleviate the congestion. However, not all generators in the system operate deterministically and independently, especially wind power generators (WTGs). Therefore, a novel optimal rescheduling model for congestion management that accounts for the uncertain and correlated power sources and loads is proposed. A probabilistic power flow (PPF) model based on 2m+1 point estimate method (PEM) is used to simulate the performance of uncertain and correlated input random variables. In addition, the impact of direct electricity purchase contracts on the congestion management has also been studied. This paper uses artificial bee colony (ABC) algorithm to solve the complex optimization problem. The proposed algorithm is tested on modified IEEE 30-bus system and IEEE 57-bus system to demonstrate the impacts of the uncertainties and correlations of the input random variables and the direct electricity purchase contracts on the congestion management. Both pool and nodal pricing model are also discussed.

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A combined framework for service identification and congestion management

Cited by 39 publications

References 9 publications

Black Hole Algorithm Implemented for Congestion Management in a Competitive Power Market

Black Hole Algorithm Implemented for Congestion Management in a Competitive Power Market

Transmission Congestion Management in Restructured Power System using Firefly Algorithm

A Congestion Management Approach Using Probabilistic Power Flow Considering Direct Electricity Purchase

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