TY - JOUR
T1 - Risk-constrained planning of rural-area hydrogen-based microgrid considering multiscale and multi-energy storage systems
AU - Shao, Zhentong
AU - Cao, Xiaoyu
AU - Zhai, Qiaozhu
AU - Guan, Xiaohong
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/3/15
Y1 - 2023/3/15
N2 - 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.
AB - 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.
KW - Data-driven linear power flow
KW - Hydrogen-based multi-energy microgrid
KW - Risk-constrained stochastic program
KW - Rural-area off-grid community
KW - Seasonal hydrogen storage
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U2 - 10.1016/j.apenergy.2023.120682
DO - 10.1016/j.apenergy.2023.120682
M3 - Article
AN - SCOPUS:85146443119
SN - 0306-2619
VL - 334
JO - Applied Energy
JF - Applied Energy
M1 - 120682
ER -