A novel meta-heuristic model for the multi-year transmission network expansion planning

Abstract

Abstract The fast construction times of projects based on variable generation technologies (VGTs) such as photovoltaic and wind generation, together with growing difficulties for building new transmission lines due to socio-environmental requirements, have opened new challenges in the development of sustainable power systems. Due to the complexity of the Transmission Network Expansion Planning (TNEP) problem, current models are usually oversimplified and do not always meet the requirements needed for the practical application. Examples of these simplifications are the use of reduced network equivalents, limiting the planning horizon to one or a few years and limiting the expansion options to adding new lines in given corridors. To meet the new challenges and achieve a time-effective increase of the transmission capacity for the integration of VGTs, improved models and algorithms capable of taking into account a higher degree of detail in the TNEP problem are needed. In this article, a novel meta-heuristic multi-year TNEP model based on Ant Colony Optimization (ACO) is presented. One of the main characteristics of the model is that it enables us to consider simultaneously further expansion options such as line reconductoring, voltage uprating, and adding series compensation to lines. We tested the proposed ACO model with the Garver’s 6-bus test system and a modified version of the IEEE\xa0118-bus test system, assuming a significant incorporation of VGTs. The results obtained for a 15-year planning task show (i) an excellent performance of the model in terms of quality of the obtained solution and computational times, compared to the traditional MILP approach, and (ii) including line uprating options within the multi-year TNEP brings significant benefits such as reducing the total investment and congestion costs of the system as well as the number of lines to be built.