Electricity-hydrogen regional integrated energy systems (EH-RIESs) are considered as one of the key paths to realize the green and low-carbon transformation of power and energy systems. However, the fault mechanism of hydrogen energy equipment hasn’t been considered by the existing reliability evaluation methods of EH-RIESs, as well as the multi-state characteristics of hydrogen energy equipment. There is no efficient reliability evaluation indexes and methods to quantify the reliability level of hydrogen supply. It means the reasonable decision-making basis for the planning and construction of EH-RIESs cannot be provided. A reliability evaluation method of EH-RIESs based on the multi-state models of hydrogen energy equipment is proposed in this paper. By accurately simulating the operation states of EH-RIESs, the reliability levels of heterogeneous energy supply are effectively quantified. Firstly, the operation characteristics and fault mechanisms of hydrogen energy equipment are analyzed. A multi-state reliability model of alkaline electrolyzers considering de-rated operation state, a multi-state reliability model of fuel cells considering cogeneration mode and a multi-state reliability model of hydrogen dispenser units are established, which provide the basic models for the operation state simulation of EH-RIESs. Secondly, an optimal load shedding model considering the coupling relationship of electricity-hydrogen heterogeneous energy systems is established to minimize the wind power and photovoltaic power curtailment costs and heterogeneous energy load reduction costs. Then, an evaluation index system of hydrogen supply reliability is constructed from the aspects of hydrogen supply reliability level, the contribution of equipment to expected hydrogen not supply and system economic loss. Finally, based on the multi-state models of hydrogen energy equipment and a Markov Chain Monte Carlo method, a reliability evaluation method is developed for EH-RIESs to quantify the reliability levels of heterogeneous energy supply. Two EH-RIESs with different scales were used to validate the effectiveness and the advantages of the proposed method. The simulation results show that after considering the de-rated operation state of hydrogenation dispenser units, the expected hydrogen not supply (EHNS) of two EH-RIESs increases by 11.82% and 17.52%, respectively. After considering the de-rated operation state of alkaline electrolyzers, the EHNS of two EH-RIESs increase by 11.44% and 5.40%, respectively. After considering the cogeneration mode of fuel cells, the expected thermal energy not supply of two EH-RIESs decrease by 81.83% and 81.01%, respectively. The hydrogen supply contribution index of electrical equipment and electrolyzers in the first EH-RIES reach 32.61% and 53.72%, respectively, which are the key factors affecting the reliability levels of hydrogen supply. In addition, with the increase of penalty cost of unit hydrogen load shedding, the economic loss of the first EH-RIES caused by electricity shortage is gradually increasing, and the comprehensive loss of energy not supply is also increasing. The following conclusions can be drawn from the simulation results. (1) The hydrogen supply reliability levels of EH-RIESs will be overestimated if the de-rated states of alkaline electrolyzers and hydrogen dispenser units are ignored. The proposed multi-state model of fuel cells considering the cogeneration mode is helpful to accurately evaluate the thermal energy supply reliability levels of EH-RIESs. (2) The proposed reliability evaluation index system and evaluation method of EH-RIESs can quantify the hydrogen supply reliability level, economic loss and the contribution of equipment failures to the hydrogen energy shortage. (3) With the increase of penalty cost of unit hydrogen load shedding, the reliability level of hydrogen supply is improved, but the reliability level of electricity supply is gradually reduced. A reasonable penalty cost of unit hydrogen load shedding is essential to balance the energy supply reliability and economic levels of systems. © 2023 Chinese Machine Press. All rights reserved.
