Presentation in IEEE-SEST 2020

Wasserstein-Distance-Based Temporal Clustering for Capacity-Expansion Planning in Power Systems

In September 2020, the $\Gamma$-opt group was present in the IEEE International Conference of Smart Energy Systems and Technologies (SEST 2020) with the work named “Wasserstein-Distance-Based Temporal Clustering for Capacity-Expansion Planning in Power Systems”. We discussed the advantages of using the Wasserstein metric to perform temporal data hierarchical clustering for the Generation, Transmission, and Storage Expansion Planning (GTSEP) optimisation.

Results show that using the metric could bring some improvements in the system’s total cost and improve the decision made for the storage capacity. The paper can be assessed here.

Lucas Condeixa
Lucas Condeixa
Doctoral Candidate

Lucas Condeixa is a Doctoral Candidate in the Systems Analysis Laboratory in the department of Mathematics and Systems Analysis in Aalto University.