A three-layer multi-objective energy scheduling for smart energy grid considering demand response and onsite energy production with hybrid energy storage systems

This paper presents three-layer multi-objective energy scheduling that are strategically situated within the framework of a smart multiple energy network (SMEN), and specifically designed to enhance and promote the optimal utilization of energy resources by consumers. The energy scheduling is meticulously modeled considering various demand response programs (DRPs) integral. The DRPs that are employed in this study include the load power shifting (LPS) and the onsite energy producing (OEP) approaches through the utilization of gas and power storage devices. At the foundational first layer of modeling, the approach to shifting power demand is intricately designed to facilitate a reduction in the overall energy bills incurred by consumers. Additionally, the OEP is modeled at the second layer, which also aims to contribute to the reduction of consumers’ energy costs, further enhancing the financial viability of the proposed methods. The third layer of the optimization process is characterized by the formulation of multi-objective functions that focus on increasing the efficiency index, improve voltage profile and minimizing operational costs, which are essential components of an efficient energy management strategy. Within this optimization framework, the third layer adeptly employs DRPs to refine and optimize energy demand in alignment with the established multi-objective functions, thereby ensuring approach to energy operation. To effectively navigate the complexities of this optimization challenge, the improved cheetah algorithm (ICA), in conjunction with TOPSIS method, is utilized to streamline the optimization process and yield meaningful results. Ultimately, the results derived from this analysis reveal the optimum rates of the various objectives and underscore the significance of active consumer participation through a comparative evaluation of two case studies. The implementation of the LPS and OEP approaches leads to improving voltage index by 3.2%, minimizing operation cost by 6.43%, and maximizing efficiency by 2.8%.