Hybrid robust-stochastic multi-objective optimization of combined cooling, heating, hydrogen and power-based microgrids

Abstract

This paper presents a holistic structure to reach the optimal operation of a combined cooling, heating, hydrogen, and power (CCHHP)-based microgrid (MG). The CCHHP-based MG under study includes a wide variety of energy conversion facilities like power-to-hydrogen (P2HY), hydrogen-to-power (HY2P), electrical chiller (EC), absorption chiller (AC), heat pump (HP), gas boiler (GB), combined heat and power (CHP), wind turbine, and energy storage systems. In the presented structure, a robust-stochastic coordinated optimization method is developed to minimize both daily operation cost and carbon pollution emissions with particular attention to uncertain sources, i.e., electricity market price, renewable power production, and energy demands. Furthermore, the incentive-based demand response (DR) program is used to increase the flexibility of the CCHHP-based MG and manage the behavior of the electrical and heating demands to use the economic opportunities in energy markets. The proposed multi-objective optimization structure is modeled as a mixed-integer linear programming (MILP) for optimal energy management using the ε-constraint method. The developed structure is solved using a CPLEX solver under the GAMS software environment. Several case studies and numerical results are provided to confirm the effectiveness of the proposed structure. Obtained simulation results indicate that utilizing the up-to-date energy conversion facilities, i.e., P2HY, HY2P, and EC, in the optimal coordinated operation with the incentive-based DR program can reduce the system operation cost to 15.44%.