Active Distribution Network Expansion Planning With Dynamic Thermal Rating of Underground Cables and Transformers

Abstract

The rapid development of renewable distributed generation in active distribution networks (ADNs) imposes an increasing burden on the transfer capability of the ADNs, bringing new challenges to the distribution network expansion planning (DNEP) problem. Dynamic thermal rating (DTR), which evaluates the equipment rating based on the actual weather conditions and equipment thermal states, can enhance the equipment transfer capability to support the integration of renewable distributed generation. In this paper, we propose a DNEP model of ADNs incorporating the DTR of cables and transformers, given that underground cable feeder is preferred in the rapid urbanization trends. Then, we derive a linear reformulation of the original DNEP model and propose a modified Benders decomposition (MBD) algorithm to solve the DNEP model. To select more effective representative day scenarios, we propose a cost-based clustering method for representative day selection applicable to solving the DNEP model. Case studies based on the IEEE 33-node system and the PG&E 69-node system show that the implementation of DTR saves 14.7% and 15.1% of the investment costs of the two systems respectively. The effectiveness of the MBD algorithm and the cost-based clustering method is also verified by the case studies.