Abstract

The optimal energy management in energy hubs has recently attracted a great deal of attention around the world. The energy hub consists of several inputs (energy resources) and outputs (energy consumptions) and also some energy conversion/storage devices. The energy hub can be a home, large consumer, power plant, etc. The objective is to minimize the energy procurement costs (fuel/electricity/environmental aspects) subject to a set of technical constraints. One of the popular options to be served as the input resource is renewable energy like wind or solar power. Using the renewable energy has various benefits such as low marginal costs and zero environmental pollution. On the other hand, the uncertainties associated with them make the operation of the energy hub a difficult and risky task. Besides, there are other resources of uncertainties such as the hourly electricity prices and demand values. Hence, it is important to determine an economic schedule for energy hubs, with an acceptable level of energy procurement risk. Thus, in this chapter a comprehensive multiobjective model is proposed to minimize both the energy procurement cost and risk level in energy hub. For controlling the pernicious effects of the uncertainties, conditional value at risk (CVaR) is used as risk management tool. The proposed model is formulated as a mixed integer nonlinear programming (MINLP) problem and solved using GAMS. Simulation results on an illustrative test system are carried out to demonstrate the applicability of the proposed method.

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