Day-ahead energy management in smart combined cooling, heating and power (CCHP) grid considering optimal consumption and local self-generation

Abstract

With growing global energy demand, ensuring a reliable energy supply is critical for all nations. The modern Energy services in residential buildings, especially those using combined cooling, heating, and power (CCHP) systems, are particularly important in meeting these demands. Accordingly, this study focuses on day-ahead energy management in a smart CCHP grid with the participation of hybrid energy storage systems and optimal energy consumption by consumers in smart residential buildings. The energy management is modeled by a multi-level and multi-objective optimization approach considering demand response strategies (DRSs). The DRSs include electrical demand shifting of power consumption, and self-generation of power, and gas storage systems. The electrical demand shifting strategy is implemented in the first level optimization, subject to electricity pricing traffic to minimize consumers’ bills. Also, minimizing consumers’ bills in the second level optimization is done by power and gas storage systems via the local self-generation (LS-G) strategy, subject to electricity and gas prices in the energy market. In the third level optimization, multi-objective functions like minimizing operational costs, maximizing flexibility and minimizing power losses are implemented. In the proposed optimization approach, optimized energy consumption in the first and second levels is considered in the third level optimization. The proposed optimization approach for all levels is solved by using General Algebraic Modeling System (GAMS) software. In the following, solving multi-objective optimization approach in the third level is carried out by enhanced epsilon-constraint method. Also, Shannon Entropy decision making method is proposed for determining optimal solution in third level for multi-objective functions and Pareto front solutions. Finally, the findings show the optimal results of the objectives at each level and highlight consumer involvement through a comparative analysis via various case studies. The participation of DRSs leads to a 11.63 % reduction in operational costs and 18.75 % reduction in power losses, while also enhancing flexibility by 2.6 % in the CCHP grid.