Multi-Constrained Optimal Power Flow by an opposition-based differential evolution

Y. Y. Chen; C. Y. Chung

doi:10.1109/PESGM.2012.6343917

Multi-Constrained Optimal Power Flow by an opposition-based differential evolution

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

8 Citations (Scopus)

Abstract

This paper proposes a robust method for solving the Multi-Constrained Optimal Power Flow (MCOPF) problem based on an opposition-based differential evolution (ODE) algorithm. The MCOPF problem, which considers transient stability, valve-point effects, prohibited operating zones, and branch flow thermal constraints, is a nonlinear, nonconvex, and nondifferentiable optimization problem in power system planning and operation, and is very difficult for conventional optimization methods to handle. The proposed ODE is an enhanced differential evolution (DE) method and employs the Opposition-Based Learning (OBL) for population initialization, production of new generations and also improving population's best fitness value. Numerical tests comparing conventional DE and ODE methods on the New England 10-generator, 39-bus system have validated the effectiveness and robustness of the proposed approach both in convergence speed and solution accuracy.

Original language	English
Title of host publication	2012 IEEE Power and Energy Society General Meeting, PES 2012
DOIs	https://doi.org/10.1109/PESGM.2012.6343917
Publication status	Published - Jul 2012
Event	2012 IEEE Power and Energy Society General Meeting, PES 2012 - San Diego, CA, United States Duration: 22 Jul 2012 → 26 Jul 2012

Publication series

Name	IEEE Power and Energy Society General Meeting
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2012 IEEE Power and Energy Society General Meeting, PES 2012
Country/Territory	United States
City	San Diego, CA
Period	22/07/12 → 26/07/12

Keywords

opposition-based differential evolution
Optimal power flow
prohibited operating zones
transient stability
valve-point effects

ASJC Scopus subject areas

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

More information

10.1109/PESGM.2012.6343917

Cite this

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title = "Multi-Constrained Optimal Power Flow by an opposition-based differential evolution",

abstract = "This paper proposes a robust method for solving the Multi-Constrained Optimal Power Flow (MCOPF) problem based on an opposition-based differential evolution (ODE) algorithm. The MCOPF problem, which considers transient stability, valve-point effects, prohibited operating zones, and branch flow thermal constraints, is a nonlinear, nonconvex, and nondifferentiable optimization problem in power system planning and operation, and is very difficult for conventional optimization methods to handle. The proposed ODE is an enhanced differential evolution (DE) method and employs the Opposition-Based Learning (OBL) for population initialization, production of new generations and also improving population's best fitness value. Numerical tests comparing conventional DE and ODE methods on the New England 10-generator, 39-bus system have validated the effectiveness and robustness of the proposed approach both in convergence speed and solution accuracy.",

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Chen, YY & Chung, CY 2012, Multi-Constrained Optimal Power Flow by an opposition-based differential evolution. in 2012 IEEE Power and Energy Society General Meeting, PES 2012., 6343917, IEEE Power and Energy Society General Meeting, 2012 IEEE Power and Energy Society General Meeting, PES 2012, San Diego, CA, United States, 22/07/12. https://doi.org/10.1109/PESGM.2012.6343917

Multi-Constrained Optimal Power Flow by an opposition-based differential evolution. / Chen, Y. Y.; Chung, C. Y.
2012 IEEE Power and Energy Society General Meeting, PES 2012. 2012. 6343917 (IEEE Power and Energy Society General Meeting).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - This paper proposes a robust method for solving the Multi-Constrained Optimal Power Flow (MCOPF) problem based on an opposition-based differential evolution (ODE) algorithm. The MCOPF problem, which considers transient stability, valve-point effects, prohibited operating zones, and branch flow thermal constraints, is a nonlinear, nonconvex, and nondifferentiable optimization problem in power system planning and operation, and is very difficult for conventional optimization methods to handle. The proposed ODE is an enhanced differential evolution (DE) method and employs the Opposition-Based Learning (OBL) for population initialization, production of new generations and also improving population's best fitness value. Numerical tests comparing conventional DE and ODE methods on the New England 10-generator, 39-bus system have validated the effectiveness and robustness of the proposed approach both in convergence speed and solution accuracy.

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Multi-Constrained Optimal Power Flow by an opposition-based differential evolution

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Keywords

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