Bi-level mixed-integer planning for electricity-hydrogen integrated energy system considering levelized cost of hydrogen. (15th July 2020)

• Record Type: Journal Article
• Authors: Pan, Guangsheng; Gu, Wei; Qiu, Haifeng; Lu, Yuping; Zhou, Suyang; Wu, Zhi
• Is Part Of: Applied energy. Volume 270(2020)
• Publication Date: 2020-07-15
• Subjects: Bi-level mixed-integer planning -- Levelized cost of hydrogen -- Electricity-hydrogen integrated energy system -- Renewable energy -- Seasonal hydrogen storage; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.115176
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Bi-level mixed-integer planning model for an energy system is presented. A price model about the levelized cost of supplying hydrogen is developed. A hybrid energy storage model with two operating modes is established. Effects of wind, solar, and geothermal energy are investigated to promote hydrogen. Abstract: Hydrogen is regarded as secondary energy that is perfectly complementary to electricity owing to its friendly storage characteristics and can play a vital role in the future low-carbon society. Toward that end, we propose a regional electricity-hydrogen integrated energy system that can achieve high penetration of renewable energy using electricity and hydrogen as energy carriers. A bi-level mixed-integer planning model is proposed to highlight the role of hydrogen in renewable energy penetration and seasonal complementarity. The upper-level model aims at improving the system economy and optimizes the equipment configuration to meet the regional energy demands; the lower-level model minimizes the levelized cost of hydrogen to promote the development of hydrogen. Both the two levels cover binary variables to characterize the interactive states and ON/OFF states, which makes the bi-level model cannot be directly translated into an equivalent mathematical program with equilibrium constraints problem. Then, a reformulation and decomposition algorithm is applied to handle this complex problem with limited iterations. Case studies show that the proposed model can achieve the dual goals of optimizing the equipment configuration and reducing the supply price of hydrogen by rationally using resources such as wind, solar, and geothermal energy in the planning stage.