A benefit-based methodology to rank transmission expansion projects

Abstract

This paper proposes a novel methodology to rank transmission expansion projects based on the benefits they provide to the system. The methodology developed estimates the benefits produced by investment projects, and is based on the idea that projects to be undertaken in a certain time horizon should be evaluated jointly instead of individually. This is due to the fact that benefits produced by each of them depend on other projects being undertaken as well. We make use of the Aumann-Shapley (AS) concept for this. AS is applied using an innovative approach whereby players in the cooperative game are investment projects instead of network users. This method, contrary to others, is able to capture the synergies among projects and the incremental impact that each project has on the total benefits of the plan. Moreover, it is highly computationally efficient and therefore, it can be applied to real power systems and big expansion plans. Two case studies are used to compare the performance of the methodology proposed to that of existing ones. The results show that the methodology proposed provides regulatory authorities with better information than other methodologies for the identification of high priority investment projects.

This paper proposes a novel methodology to rank transmission expansion projects based on the benefits they provide to the system. The methodology developed estimates the benefits produced by investment projects, and is based on the idea that projects to be undertaken in a certain time horizon should be evaluated jointly instead of individually. This is due to the fact that benefits produced by each of them depend on other projects being undertaken as well. We make use of the Aumann-Shapley (AS) concept for this. AS is applied using an innovative approach whereby players in the cooperative game are investment projects instead of network users. This method, contrary to others, is able to capture the synergies among projects and the incremental impact that each project has on the total benefits of the plan. Moreover, it is highly computationally efficient and therefore, it can be applied to real power systems and big expansion plans. Two case studies are used to compare the performance of the methodology proposed to that of existing ones. The results show that the methodology proposed provides regulatory authorities with better information than other methodologies for the identification of high priority investment projects.