An efficient optimization framework for distribution network planning by simultaneous allocation of photovoltaic distributed generations and transformers

Abstract

Among the distribution network planning problems, allocation of transformers is one of the most important and challenging ones. On the other hand, owing to the widespread growth of distributed generations (DGs), their inclusion in the planning problems is vital. This paper proposes an efficient optimization framework for simultaneous allocation of photovoltaic (PV) systems and service transformers in the distribution network. For this aim, to improve the network performance, location and size of the transformers and PV units are optimally determined. Due to the difficulty of the planning problem, four variants of crow search algorithm (CSA) including original CSA, differential CSA (CSAd), directed differential CSA (CSAdd) and chaotic directed differential CSA (CSAcdd) are introduced and applied to the planning problem. To evaluate the impact of PV cost on the results, the planning problem is solved considering different PV system costs. Simulation results show that at the price of $1.25/W, installation of PV systems is cost‐effective, so that over the case study, 400 kW PV system was installed. By decreasing the PV price to $1.2/W, the maximum capacity considered for a PV system is installed. Moreover, on average, CSAd produces more accurate and robust results than the other studied algorithms.

A risk‐averse strategy based on information gap decision theory for optimal placement of service transformers in distribution networks

“…No uncertainty has been regarded in the models. In [9], an optimization framework has been introduced to simultaneously allocate photovoltaics (PVs) and service transformers in the distribution network. It can be seen that the integration of PVs can considerably affect the size and site of service transformers.…”