Energy scheduling based-two layers interval optimization in a smart energy hub system with multi-performance of the hydrogen storage system and demand side management

Abstract

A smart energy hub (SEH) is one of the significant opportunities in smart grids as a distinguished framework for optimal energy consumption and generation. The energy price uncertainty in energy markets for energy optimization is the main challenge for achieving economic modeling of energy consumption and generation. This paper proposes optimal energy scheduling in a SEH under uncertainty of electricity prices in the day ahead in the energy market. The proposed optimization approach is implemented by a two-layer interval approach considering uncertainties for minimizing energy generation cost. In first layer optimization, electrical demand subject to the optimal level of electrical consumption is modified by the demand shifting strategy by using the demand side management (DSM). In second-layer optimization, the interval approach is used for modeling uncertainty; and energy generation cost is converted to Bi-objective functions including average and deviation costs with conflict nature than each other. Also, the multi-performance of the hydrogen storage system based-electrical and natural gas generation is considered for managing uncertainties in second layer optimization. Since the interval optimization approach is proposed in the second layer, minimizing the average cost and deviation cost are formulated as Bi-objective functions by the augmented epsilon-constraint method. In the following, the LINMAP procedure is utilized to achieve maximum compatibility and the best trade-off consequence in the Pareto frontier of the multi-objective functions. Finally, the proposed optimization approach is modeled as a numerical simulation in the three case studies to verify obtained results by implementing the DSM and hydrogen storage system participation.