Transmission Expansion Planning

Abstract

A critical issue in the operation of electric energy systems is the capacity of the transmission lines that enable energy flows from generation nodes to demand nodes. In this chapter, we analyze the transmission expansion planning (TEP) problem, which allows a transmission planner to identify the optimal transmission reinforcements to be carried out with the aim of facilitating energy exchange among producers and consumers, e.g., by reducing generation or load-shedding costs. With this purpose, two models are described and analyzed: first, a deterministic model that solves the TEP problem based on a future demand forecast, and second, an adaptive robust optimization (ARO) model that takes into account the influence of different sources of uncertainty, such as future demand growth and the availability of generating units in the TEP problem. These two models are formulated using a static approach in which transmission expansion plans are made at a single point in time and for a future planning horizon. 2.1 Introduction This chapter analyzes the transmission expansion planning (TEP) problem, which refers to the decision-making problem of determining the best transmission reinforcements to be made in an existing electric energy system. TEP is motivated, among other reasons, by the aging of the current infrastructure [20], expected demand growth, and the building of new renewable production facilities, usually located far away from demand centers. These issues make it essential to reinforce and to expand the existing transmission network in order to facilitate energy exchanges among producers and consumers as well as to guarantee supply-demand balance. TEP is a critical issue in modern electric energy systems because transmission lines allow energy flows from generating to demand nodes. These demands must be supplied even in the worst situations, e.g., those corresponding to a peak load or the failure of a generating unit. Thus, transmission expansion plans should be decided in such a way that demands are efficiently supplied even if one of these situations