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Highlights: [•] We develop an energy hub by wind, storage and demand response in distribution network. [•] We present two objective functions for the hub operation under certainty and uncertainty of wind, price and demand. [•] We consider operation costs, emission and reliability in the objective function. [•] We apply two stage stochastic programming of GAMS for solving the hub MILP model under uncertainty. [•] We evaluate effect of DERs and the uncertainties on hub operation costs and reliability in nine cases. [Copyright &y& Elsevier]

Abstract: Feeder reconfiguration is one of the most important tasks for loss reduction and reliability improvement in distribution networks. Most of studies so far have investigated reconfiguration problem as a static problem considering fixed level of loads. This assumptions lead to suboptimal solution because of time-varying nature of loads in distribution networks. The switching operation should be cost effective and the reconfiguration scheme should balance the benefits in system loss reduction and reliability improvement against the costs of switching. Moreover, this is a dynamic problem and switching operations of time intervals over a year are not independent. This paper presents a method to determine annual feeder reconfiguration scheme considering switching costs and time-varying variables such as load profiles. In the first stage of the proposed method, to obtain effective configurations, optimal configuration for each day of year is determined independently using harmony search algorithm (HSA) and graph theory. After determination of effective configurations for the network, in the second stage, year is divided into multi equal periods and considering loss cost, interruption cost and also switching cost from a configuration to another configuration, dynamic programming algorithm (DPA) is used to find the optimum annual reconfiguration scheme. The proposed method has been tested on 95-bus distribution network and the obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically. [Copyright &y& Elsevier]