Carbon emission flow oriented multitasking multi‐objective optimization of electricity‐hydrogen integrated energy system

A grid-connected electricity-hydrogen integrated energy system (EH-IES) is proposed here for the cooperative analysis of electricity, heat, cooling and hydrogen flows, where carbon emission flow (CEF) introduced to allocate emission. Simultaneously, an improvement multitasking multi-objective optimization (MT-MOO) algorithm applied optimize operation this EH-IES. The EH-IES optimizes operational cost, dioxide loss while considering uncertainties future demand, wind photovoltaic (PV) power outputs. CEF model among EH-IES, which can calculate in flow. In order solve MOO model, a MT-MOO utilize implicit information different tasks. However, there are harmful interactions between tasks when relativity low. Therefore, paper introduces online learning random mating probability method calculates transformation extent Simulation results show that has good feasibility efficiency, better convergence performance than comparing intelligence algorithms.