A multi-slack optimization model for scheduling energy hubs in smart grids

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.

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Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).