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A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow

A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow

Sourav Paul, Provas Kumar Roy
Copyright: © 2016 |Pages: 30
ISBN13: 9781466697553|ISBN10: 1466697555|EISBN13: 9781466697560
DOI: 10.4018/978-1-4666-9755-3.ch007
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MLA

Paul, Sourav, and Provas Kumar Roy. "A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow." Sustaining Power Resources through Energy Optimization and Engineering, edited by Pandian Vasant and Nikolai Voropai, IGI Global, 2016, pp. 147-176. https://doi.org/10.4018/978-1-4666-9755-3.ch007

APA

Paul, S. & Roy, P. K. (2016). A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow. In P. Vasant & N. Voropai (Eds.), Sustaining Power Resources through Energy Optimization and Engineering (pp. 147-176). IGI Global. https://doi.org/10.4018/978-1-4666-9755-3.ch007

Chicago

Paul, Sourav, and Provas Kumar Roy. "A Novel Optimization Algorithm for Transient Stability Constrained Optimal Power Flow." In Sustaining Power Resources through Energy Optimization and Engineering, edited by Pandian Vasant and Nikolai Voropai, 147-176. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9755-3.ch007

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Abstract

Optimal power flow with transient stability constraints (TSCOPF) becomes an effective tool of many problems in power systems since it simultaneously considers economy and dynamic stability of power system. TSC-OPF is a non-linear optimization problem which is not easy to deal directly because of its huge dimension. This paper presents a novel and efficient optimisation approach named the teaching learning based optimisation (TLBO) for solving the TSCOPF problem. The quality and usefulness of the proposed algorithm is demonstrated through its application to four standard test systems namely, IEEE 30-bus system, IEEE 118-bus system, WSCC 3-generator 9-bus system and New England 10-generator 39-bus system. To demonstrate the applicability and validity of the proposed method, the results obtained from the proposed algorithm are compared with those obtained from other algorithms available in the literature. The experimental results show that the proposed TLBO approach is comparatively capable of obtaining higher quality solution and faster computational time.

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