Risk-constrained planning of rural-area hydrogen-based microgrid considering multiscale and multi-energy storage systems

• Published in: Applied energy Vol. 334; p. 120682
• Main Authors: Shao, Zhentong, Cao, Xiaoyu, Zhai, Qiaozhu, Guan, Xiaohong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.03.2023
• Subjects: Data-driven linear power flow; Hydrogen-based multi-energy microgrid; Risk-constrained stochastic program; Rural-area off-grid community; Seasonal hydrogen storage; Data-driven linear power flow; Seasonal hydrogen storage; Risk-constrained stochastic program; Hydrogen-based multi-energy microgrid; Rural-area off-grid community
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2023.120682

Recent advances in renewable hydrogen production and storage technologies have offered a promising path towards the carbon-neutral energy supply of rural communities. This paper presents a risk-constrained planning method for hydrogen-based multi-energy off-grid microgrids under economics and resilience considerations. A two-stage risk-constrained stochastic programming formulation is proposed, which is to optimize the energy resources configuration in the first stage, and conducts long-term economic dispatch as well as the on-emergency feasibility verification in the second stage. Sophisticated analytical models are developed to coordinate the operations of multi-timescale and multi-energy storage facilities (especially the short-term and seasonal hydrogen storage). Also, the risk constraints are imposed via sampling approximation strategy to control the risks of crucial components failures for resilience enhancement. Moreover, through the data-driven power flow linearization, our planning problem can be recasted as a mixed-integer linear program (MILP), and efficiently computed by developing a dual cutting-plane based enhanced decomposition algorithm. Numerical studies on a real-world rural energy system in Southwestern China validates the effectiveness of the proposed planning method. It has significantly reduced the levelized system costs through seasonal storage deployment and multi-energy synergy. Besides, our customized solution algorithm demonstrates a strong scalable capacity that support planning decisions under complex uncertainties. •A hydrogen-centered multi-energy microgrid is designed for rural areas.•Multiscale and multi-energy storage systems are analytically modeled.•A risk-constrained stochastic formulation is proposed for microgrid planning.•Data-driven linearization method and enhanced decomposition algorithm are developed.•Methods application and verification on a real-world rural microgrid.