Optimal probabilistic based storage planning in tap-changer equipped distribution network including PEVs, capacitor banks and WDGs: A case study for Iran

Due to their cost-effective and environmental-friendly natures, renewable energies as well as Plug-in Electric Vehicles (PEVs) are increasingly utilized nowadays. A critical challenge with renewable energies is natural intermittency and as such can be addressed appropriately using Energy Storage Systems (ESS). In this paper, optimal planning of battery based energy storage units is proposed in distribution network. As an important challenge in optimal storage planning, the uncertainty investigation is dealt with in this work. A new approach which is based on Point Estimate Method (PEM) is introduced as a tool to handle the uncertainty of the load, the Wind-based Distributed Generation (WDG) and PEVs demand, simultaneously. The proposed method is intuitively compared with Monte Carlo Simulation (MCS) as well as conventional PEM for a case study and the results are verified through the comparisons. Moreover, in order to challenge voltage control benefit of the storage units, the under study distribution network is equipped to the tap-changer and the capacitor banks. Whereas the optimal storage planning is a very complicated task, a modified hybrid Particle Swarm Optimization (PSO) and Tabu Search (TS) algorithm is used to solve the related optimization problem. The simulation results for a case study in Iran show the effectiveness of the proposed approach in different scenarios.