Optimal operation of energy hub system using hybrid stochastic-interval optimization approach

Abstract This study proposes a hybrid interval-stochastic framework to create robust programming of energy hub which thermal energy market, thermal demand response program (TDRP) and electrical demand response program (EDRP) are considered to manage flexible energy management in order to reduce operation cost. In the proposed work, deviation cost is added to objective function in addition to average cost as a bi-objective model which weighted sum method is applied to reformulate as a single objective function and optimal Pareto solutions are obtained with varying weight coefficients. Then, a fuzzy satisfying approach is applied to get the trade-off result from Pareto solutions. The proposed model is formulated as mixed-integer linear programming (MIP) model which can be solved using CPLEX solver under GAMS optimization software. The proposed model is applied to a sample energy hub to show the capability of the proposed hybrid interval-stochastic framework. The compared results conclude that the average cost is leisurely raised while deviation cost is severely decreased which leads to obtaining robust scheduling of hub energy system in the uncertain environment. Finally, TDRP and EDRP are implemented to manage peak thermal and electrical demands which lead to reducing the average and deviation costs of the hub energy.