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This paper develops a new model for the optimal placement of switches (both manual and automatic ones) in distribution networks to simultaneously reduce energy loss and improve network security. Expected energy not supplied (EENS) is assumed as the security index, and a method is developed for more exact calculation of this index regarding drastic climatic changes along with global warming and the resultant effects on both power consumption patterns and power network occurrence. The objective function of the problem is minimizing investment and maintenance costs, the cost of energy loss, and EENS cost. The suggested model can locate optimal places for installing the switches and their seasonal closed and open states so that the total costs can be minimized. The model is implemented on two test networks and evaluated under different scenarios. According to the results, despite the higher costs of automatic switches, the application of automatic switches is more economical in low-security networks for improving network security. [ABSTRACT FROM AUTHOR]

This paper provides a multi-slack optimization model in order to manage the operation of an energy hub in smart grids. This model is centralized on a multi-slack one in which the proposed slack variables are in line with actual energy providers. Both electrical and thermal loads are considered in this model. An external grid and boilers are respectively used for slack generation units for satisfying electrical and thermal loads. In order to reduce the penalty factors in the optimization model, we addressed fair and suitable slack variables in the optimization model. In a real power system, energy storage devices could effect optimal operation in short-term planning. The main role of such devices in smart grids is to reduce the operating costs because of their state of charge (SOC) in peak, medium and base loads. Such devices could also handle load and generation uncertainties in the real world. In this model, we implement this feature to handle the uncertainties in the random variable generation sector of optimization algorithm. The proposed method could handle this challenge by discharging the stored energy if the slack unit is unable to satisfy the demanded load and vice versa. In order to evaluate the effectiveness of the proposed method, a benchmark is provided in this paper. The hourly electrical and thermal demands were extracted from DesignBuilder® for a commercial building. The simulation results show that the presented method is both satisfactory and consistent with expectations. [ABSTRACT FROM AUTHOR]