An investigation of reactive power planning based on chance constrained programming

Deregulation in the electricity supply industry has brought many new challenges to the problem of reactive power planning. Although the problem has been extensively studied, available standard optimization models and methods do not offer good solutions to this problem, especially in a competitive el...

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Bibliographic Details
Published in:International journal of electrical power & energy systems 2007-11, Vol.29 (9), p.650-656
Main Authors: Yang, Ning, Yu, C.W., Wen, Fushuan, Chung, C.Y.
Format: Article
Language:English
Subjects:
Applied sciences
Chance constrained programming
Electrical engineering. Electrical power engineering
Electrical power engineering
Exact sciences and technology
Genetic algorithm
Monte Carlo simulation
Operation. Load control. Reliability
Power networks and lines
Reactive power planning
Uncertainties
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Summary:Deregulation in the electricity supply industry has brought many new challenges to the problem of reactive power planning. Although the problem has been extensively studied, available standard optimization models and methods do not offer good solutions to this problem, especially in a competitive electricity market environment where many factors are uncertain. Given this background, a novel method for reactive power planning based on chance constrained programming is presented in this paper, with uncertain factors taken into account. A stochastic optimization model is first formulated under the presumption that the generator outputs and load demands can be modeled as specified probability distributions. A method is then presented for solving the optimization problem using the Monte Carlo simulation method and genetic algorithm. Finally, a case study is used to illustrate the validity and essential features of the proposed model and methodology.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2006.09.008