This paper presents a shrinking-horizon optimization framework for energy hub scheduling in the presence of wind turbines, storage systems and flexible loads. The uncertainties of wind turbine output power and electricity price are considered in the model and in order to model them, the shrinking-horizon method is utilized. The proposed hub is able to exchange power, heat and gas with the network at its input and supplies electrical, heating and cooling demands at the output. In addition, an integrated demand response (IDR) program is included in the model to increase system flexibility and modify the load demand curve. The objective function is to minimize the operating cost and emissions and is modeled as a mixed-integer non-linear programming (MINLP) problem, solved by DICOPT solver in GAMS software. The simulation results demonstrate that increasing the flexible loads reduces the purchase of power and heat from the network during peak hours and thus leads to a reduction in operating cost. Numerical results show that a 7% and 12% increase in flexible loads reduces the total operating cost by 5% and 7%, respectively. In addition, this problem was solved by stochastic and shrinking-horizon methods, the results substantiate that the use of shrinking-horizon method has led to more accurate and optimal results.
کلید واژگان :Energy hubShrinking-horizon methodIntegrated demand response programsWind turbineEnergy storage systemsUncertainty
ارزش ریالی : 500000 ریال
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