Transmission Network Expansion Planning Considering Uncertainty in Demand with Global and Nodal Approach

Abstract

Transmission expansion planning aims to establish when and where to install new infrastructure such as transmission lines, cables, generators and transformers in the electrical power system. The planning must be motivated mainly to satisfy the increase in demand, consequently increase the reliability of the system and provide non-discriminatory access for generators and consumers to the electrical grid. In this sense, this work aims to propose a methodology to handle demand uncertainty by reducing scenarios through the K-means clustering algorithm, which is used to construct representative demand curves that allow using a static model of stochastic linear optimization with less computational effort, which seeks to minimize the investment and operating costs of the electrical system, meeting the total demand of the system. The global demand and nodal demand approach of the system is compared, observing the behaviour of investment and operating costs, as well as their advantages. The results demonstrate that the formulation can be estimate the number of scenarios through mathematical metrics and the global demand approach has the advantage of only needing data on the behavior of the total demand of the system.