Optimum Allocation of Service Transformers in the Presence of Renewable Energy‐Based Distributed Generations Considering Different Load Profiles

ABSTRACT Renewable energy resources (RERs)‐based distributed generations (DGs) such as wind turbines (WTs) and photovoltaics (PVs) are being widely used worldwide, and it is important to consider their impact on the distribution network planning (DNP) problems. In a distribution network, there are many service transformers, and it is vital to consider the impact of RERs on the optimum location and capacity determination of these transformers. Since the shapes of load profiles and RERs generation may highly affect the planning results, in this paper, simultaneous planning of service transformers, PVs and WTs is investigated with respect to different load profiles. Due to the complexity of this problem, the crow search algorithm (CSA), particle swarm optimisation (PSO), differential CSA and a novel method which combines CSA and PSO (CSA‐PSO) are applied, and a comparison of the results is performed. To validate the performance of CSA‐PSO, a sensitivity analysis is conducted on the key parameter of the algorithm. Over the case study, it is observed that (1) the shape of the load profile and local RER generation significantly influence the placement and capacity of service transformers, (2) compared to a PV system, due to its lower cost and better correlation with the load profile, aWT system is preferable and is installed in the network, and (3) CSA‐PSO and differential CSA produce better results than the other investigated methods. Furthermore, over the studied load profiles, the average ratio of the installed WT capacity to the total transformers’ capacity is around 28.3%.