Decision support methods for large-scale flexible transmission expansion planning

Abstract

In order to integrate the new generation that will be installed in the coming decades, it will be necessary to upgrade the existing transmission network. Transmission Expansion Planning (TEP) is a complex problem in itself that has been further challenged in the current environment. We develop techniques to support decision making in this context. We make contributions in modeling (such as our compact HVDC formulation), problem resolution (such as semi-relaxed cuts) and in the interpretation of results (such as our candidate develop a Progressive Contingency Incorporation algorithm to perform stochastic optimization where scenarios describe element failures). We develop a Real Options Valuation approach to TEP that focuses on finding flexible expansion strategies. We extend he concept of shrinkage to develop robust expansion plans. We propose a candidate discovery technique to detect and analyze potentially interesting candidate lines. Last, we develop a hybrid of Ordinal Optimization and MIP that exploits problem structure.