Acceleration strategies of Benders decomposition for the security constraints power system expansion planning

M. Jenabi, S. Fatemi Ghomi (), S. Torabi and S. Hosseinian

Annals of Operations Research, 2015, vol. 235, issue 1, 337-369

Abstract: Nowadays the power generation and transmission are substantial elements for the society, and will definitely play a more important role in the future. In this paper a modeling framework is presented to analyze security constrained composite generation and transmission expansion planning problem in power systems. Despite of the traditional expansion planning approaches where only supply side options are considered, the proposed approach accounts for both supply and demand side management (DSM) options simultaneously. DSM options are incorporated to correct the shape of the load duration curve in terms of peak clipping and load shifting programs. A mixed integer non-linear programming model is developed to find the optimal location and timing of electricity generation/transmission as well as DSM options while the effect of transmission losses are also taken into account. Nonlinearity of the transmission loss terms is eliminated using the piecewise linearization. Motivating from the structure of the model, Benders decomposition (BD) algorithm is devised. Three effective strategies named: valid inequalities, multiple generation cuts and strong high density cut are also employed to improve the convergence of the proposed BD algorithm. The performance of the accelerated BD algorithm is validated via applying it to the modified 6, 21, 48, 57, 118 and 300 bus IEEE reliability test systems. The computational experiments ensure the practicality of the proposed BD algorithm in terms of decreasing the number of iterations and CPU times. Copyright Springer Science+Business Media New York 2015

Keywords: Composite generation and transmission planning; Power systems; Demand side management; Transmission loss; Accelerated Benders decomposition (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10479-015-1983-5

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