Multi-objective optimization for an integrated renewable, power-to-gas and solid oxide fuel cell/gas turbine hybrid system in microgrid

Power-to-gas (P2G) using excess renewable sources is an effective method to reduce renewable curtailment issues in microgrid system. The produced hydrogen is versatile green fuel for different energy sectors, such as electricity, heat and mobility. In recent researches, fuel cell-based system is considered as a promising technology to consume hydrogen (H2) generated from P2G due to high efficiency and cleanness. However, its economic and thermodynamic adaptability when coupled with intermittent renewable sources remains an open question to be addressed carefully. One of the major challenges in optimizing such system is to simultaneously capture the intraday and seasonal variation of renewable sources & load, as well as the internal thermodynamic process of critical components in appropriate modeling detail. This paper presents a multi-energy system for microgrid in which a wind-powered P2G is coupled with a detailed thermoeconomic model of solid oxide fuel cell/gas turbine (SOFC/GT) hybrid system. A two-level multi-objective optimization of planning and operation together is proposed. For system planning, the optimal balance between the least wind curtailment rate and total life cycle cost (LCC) is determined. To facilitate the coordinate operation of system components, a power management strategy is proposed in response to fluctuations of wind power and electricity load with considerations of multiple thermodynamic safety criteria. Results show that in the selected case, the multi-energy system operates with low wind curtailment rate of 0.63% and high renewable penetration level of 90.1%. The optimized LCC of multi-energy system is 2,468,093 with wind power accounting for 68.35% of total capital investment. With the power management strategy applied, the SOFC/GT could operate under the maximum electrical efficiency of 67.1% with safety constraints satisfied, making up only half investment cost of P2G. To capture seasonal variations, both winter and summer scenarios are detailly analyzed, sensitivity analysis is also carried out to evaluate the interaction between capacities of MES components. (C) 2020 Elsevier Ltd. All rights reserved.