An Emission and Uncertainty Aware Optimal Dispatch of Multi-Energy Hub

The integration of different energy carriers within a smart energy system with a significant presence of renewable energy sources (RES), such as wind energy conversion system (WECS), and solar photovoltaic (PV) system has made the energy hub (EH) a crucial component. The efficient management and coordination of EH's resources play a critical role in meeting kinds of energy demand at a minimal cost and achieving environmentally sustainable operation. In pursuit of these objectives, this study presents an economic-environmental EH framework that incorporates a substantial integration of RES. The EH comprises solar PV, WT, combined heat and power (CHP) unit, battery energy storage system (BESS), heat energy storage system (HESS), electric heat pump (EHP), electric boiler (EB), heat furnace (HF), absorption chiller (AC), and electric chiller (EC). The Monte-Carlo (MC) approach has been used to forecast the uncertainties (scenario generation) associated with RES, various types of energy consumption, electricity, and gas prices. The Kantorovich algorithm is employed for scenario reduction. The proposed framework is formulated as a multi-objective (MO) stochastic mixed-integer non-linear programming (MINLP) problem and solved using BARON solver in GAMS software. The simulation study validates the proposed model of EH.