As a result of the recent innovations in deployment of plug-in electric vehicles (PEVs), this technology can play an important role as a distributed energy resource (DER) in supplying the system demand of the power systems of the future. This paper, introduces a methodology for optimal coordinated allocation of wind farms (WFs), energy storage systems (ESSs) and PEV's parking lots (PEV-PLs) considering demand response programs (DRPs) and hourly distribution network reconfiguration (DNR) in normal and severe contingency conditions. In the proposed methodology, participation of different types of loads is also examined. The objective function is to minimize the total costs of purchased power from upstream network and WFs, along with the costs of commercial/industrial loads flexibility and residential loads curtailment. To validate the performance of proposed methodology, it is implemented on the well-known IEEE 33-bus distribution test system. The simulation results, validate the feasibility and effectiveness of the proposed approach.

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This study proposes a two-stage stochastic optimisation model for jointly wind turbine (WT) allocation and network reconfiguration (NR) so as to increase the resiliency of distribution system in face of natural disasters. In this regard, in the first level, a possibilistic-scenario method is proposed to select the line outage scenarios. The proposed model is capable with distribution systems and considers different failure probabilities for system components subject to the intensity of natural disaster in its associated zone. After selecting the line outage scenarios, in the second level, a multi-stage optimisation framework is proposed for jointly NR and WT allocation in a multi-zone and multi-fault system, considering the uncertainty of system load and wind power generation. This strategy makes an interconnection between NR and islanded WTs to increase the resiliency of system and decreases the load shedding. Different economic objectives including, costs of load shedding and power generation are considered in the model. In addition, hardening budget is taken into consideration for the transmission lines, which is minimised during the optimisation process. The simulation results demonstrate the capability and necessity of proposed resiliency-oriented method and prove the importance of hardening budgets.

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