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Stochastic security-constrained generation expansion planning methodology based on a generalized line outage distribution factors

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conference contribution
posted on 13.07.2017 by Victor H. Hinojosa, Francisco Gonzalez-Longatt
In this study, the authors proposes to develop an efficient formulation in order to figure out the stochastic security-constrained generation capacity expansion planning (SC-GCEP) problem. The main idea is related to directly compute the line outage distribution factors (LODF) which could be applied to model the N − m post-contingency analysis. In addition, the post-contingency power flows are modeled based on the LODF and the partial transmission distribution factors (PTDF). The PTDF-based generation capacity planning formulation has been reformulated in order to include the post-contingency constraint solving both pre- and post-contingency constraints simultaneously. The methodology includes in the optimization problem the load uncertainty using a two-stage multi-period model, and a K−means clustering technique is applied to reduce the load scenarios. The main advantage of this methodology is the feasibility to quickly compute the post-contingency factors especially with multiple-line outages (N − m). This idea could speed up contingency analyses and improve significantly the security-constrained analyses applied to stochastic GCEP problems. It is conducted several experiments with two electrical power systems in order to validate the performance of the proposed formulation.

Funding

This study was supported in part by the Chilean National Commission for Scientific and Technological Research (CONICYT) under grant Basal FB0008, and by the Universidad Tecnica Federico Santa Maria, Chile, under project USM 116.22.2.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Powertech 2017

Citation

HINOJOSA, V.H. and GONZALEZ-LONGATT, F.M., 2017. Stochastic security-constrained generation expansion planning methodology based on a generalized line outage distribution factors. IEEE PowerTech 2017, Manchester, UK, 18th-22nd June 2017.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

01/05/2017

Publication date

2017

Notes

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

en

Location

Manchester, UK

Exports