NDLI: A formulation for large-scale transmission expansion planning problem and a solution strategy

Content Provider	IEEE Xplore Digital Library
Author	Desta Zahlay, F. de Cuadra, F. Olmos, L. Rivier, M. Perez-Arriaga, I.J.
Copyright Year	2013
Description	Author affiliation: Inst. for Res. in Technol. (IIT), Comillas Univ., Madrid, Spain (de Cuadra, F.; Olmos, L.; Rivier, M.; Perez-Arriaga, I.J.) \|\| Electr. Power Syst. Dept., R. Inst. of Technol. (KTH), Stockholm, Sweden (Desta Zahlay, F.)
Abstract	The expected deployment of massive renewable energy sources (RES, mainly of wind and solar) at a continental or even intercontinental level creates very complex transmission expansion planning (TEP) problems. Both the size of the system and the level of uncertainty are huge. Solving a TEP problem for such big networks under high levels of uncertainty demands an exceptionally huge computational effort when using reasonably precise models. Conventional modeling approaches and solution strategies cannot be directly reproduced in this case due to their computational limitations. In this paper, we show a systematic way of approaching the problem, which deals both with modeling and with solution strategy aspects. We formulate the TEP problem as a two period stochastic linear programming problem characterized by common investment decisions to all scenarios in the first period and scenario-dependent decisions in the second period. In order to make it tractable, we devise a solution strategy based on decomposing the problem into successive optimization phases. Each phase uses the results of the previous one to reduce the search space. This reduction in complexity allows each phase to use more complex models with a similar computational load. Each optimization phase could be defined and solved as an independent problem, thus, allowing the use of specific decomposition techniques, or parallel computation when possible. A modified Garver's system is used to illustrate the methodologies. Test results from IEEE-300 bus system show that the proposed solution strategy is very effective. And, integrating the proposed solution strategy in the solution process contributes to a significant reduction in computational effort while fairly maintaining optimality of the solution.
Starting Page	1
Ending Page	8
File Size	1177977
Page Count	8
File Format	PDF
ISBN	9781479920082
ISSN	21654093
DOI	10.1109/EEM.2013.6607393
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-27
Publisher Place	Sweden
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	renewable energy sources Computational modeling stochastic programming solution strategy Indexes Transmission expansion planning
Content Type	Text
Resource Type	Article

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