Capacity optimization and economic analysis of PV–hydrogen hybrid systems with physical solar power curve modeling

• Published in: Energy conversion and management Vol. 288; p. 117128
• Main Authors: Yang, Guoming, Zhang, Hao, Wang, Wenting, Liu, Bai, Lyu, Chao, Yang, Dazhi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.07.2023
• Subjects: administrative management; carbon; China; climate; Economic analysis; electricity; energy conversion; Hydrogen; hydrogen production; issues and policy; Model chain; PV–hydrogen hybrid systems; solar energy; solar farms; Solar power curve; China; TMY; Economic analysis; BHI; STC; DHI; HFC; Solar power curve; SPA; Hydrogen; PV; GHI; MPP; NREL; ECMWF; NPV; NOCT; HFV; NSRDB; DOE; PV–hydrogen hybrid systems; CEC; AST; POA; NIC; PSM; IMS; LCOE; MODIS; AR; LCOH; O&M; PEM; Model chain; API; BNI; GTI
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2023.117128

Using photovoltaic (PV) power for hydrogen production presents an alluring prospect under humanity’s ongoing pursuit of carbon neutrality by mid of this century. An indispensable initial step in commissioning PV–hydrogen hybrid systems involves analyzing in-depth its capacity configuration, operation strategy, and economic benefits. With the objective of maximizing the annual profit of such systems, this work formulates a capacity optimization model and performs related economic analysis, with pre-determined installed capacity and plant layout. Two aspects distinguish this work from its predecessors: (1) The physical (i.e., model chain) modeling of PV is employed to narrate the behavior of the PV plant in a more refined fashion, and (2) the impact of government support on the configuration and economics of PV–hydrogen hybrid systems is analyzed by incorporating into the objective function environmental benefits subsidized by the government. Besides, sensitivity analysis is conducted for numerous parameters that can affect the configuration outcome. The proposed model is applied under the climate regime of Heilongjiang Province, China, and the veracity and validity of the proposed model are verified via case studies. The results reveal that a 1-MW PV plant requires a transformer of 226.9 kW, electrolyzers of 366.8 kW, and 3 compressors, when the physical modeling of PV is utilized. The exorbitant investment cost of hydrogen tanks and hydrogen fuel cells renders these devices unsuitable for use in PV–hydrogen hybrid systems. The advantages of physical modeling of PV enable an increase of 38.9% in the annual profit of the hybrid systems, compared to the conventional modeling of PV using only surrogate equations. Furthermore, it is found that government subsidy policy, various prices and costs, and the utilization rate of PV power are among the most influencing factors affecting the optimal capacity and economics of the hybrid systems. In solar-rich areas of Heilongjiang, it is preferable to equip electrolyzers with a larger capacity and to install a transformer with a smaller rating power, to achieve a higher annual profit. The levelized cost of electricity of PV–hydrogen hybrid systems is 0.03 $/kWh, the levelized cost of hydrogen is 2.9 $/kg, and the payback time is ∼11 years. These results could serve as a benchmark for future PV–hydrogen hybrid system development, and offer information that is of interest to policymakers, operators, and investors, thereby contributing to the realization of zero-carbon energy systems. •Sizing and economic analysis of PV–hydrogen hybrid systems are conducted.•The model involving the physical modeling of PV is verified in Heilongjiang, China.•Refined modeling of PV increases the annual profit by up to 38.9%.•The impact of government policy on equipment specs and economics is substantial.•The payback time of PV–hydrogen hybrid systems is ∼11 years.