TY - JOUR
T1 - Techno-economic risk-constrained optimization for sustainable green hydrogen energy storage in solar/wind-powered reverse osmosis systems
AU - Ba-Alawi, Abdulrahman H.
AU - Nguyen, Hai Tra
AU - Aamer, Hanaa
AU - Yoo, Chang Kyoo
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/6/15
Y1 - 2024/6/15
N2 - Hydrogen energy storage systems (HESSs) are vital for enhancing the resilience of energy systems and coping with the intermittency of renewable energy sources. However, their implementation presents significant risks and costs. This study proposes a novel safety-oriented multi-criteria optimization approach for designing sustainable HESSs tailored to meet the demands of a hybrid solar-wind powered reverse osmosis system. Firstly, a hybrid deep-learning model was developed to enhance the precision of weather and demand data forecasting. Subsequently, a comprehensive qualitative–quantitative risk assessment was conducted to explore the impact of HESS design parameters, including storage size, pressure, flow rate, and temperature. Then, multi-objective optimization was performed considering the total environmental cost, total life cycle cost (TLCC), and risk cost index (RCI). The design of three green HESSs, gas hydrogen storage (GH2), liquid hydrogen storage (LH2), and material-based hydrogen storage (MH2), were compared. The results reveal that GH2 has the largest TLCC (568,164.60 USD/year), followed by MH2 (460,674.18 USD/year) and LH2 (383,895.25 USD/year) The RCI identifies LH2 (0.21) as the highest risk, primarily because of the potential explosion hazards. Although MH2 integration may offer cost and safety advantages, temperature control during hydrogen release poses challenges to its practical application. Thus, this study offers a balanced approach integrating safety and economic considerations for designing green HESSs, aiding decision-makers toward sustainable energy solutions.
AB - Hydrogen energy storage systems (HESSs) are vital for enhancing the resilience of energy systems and coping with the intermittency of renewable energy sources. However, their implementation presents significant risks and costs. This study proposes a novel safety-oriented multi-criteria optimization approach for designing sustainable HESSs tailored to meet the demands of a hybrid solar-wind powered reverse osmosis system. Firstly, a hybrid deep-learning model was developed to enhance the precision of weather and demand data forecasting. Subsequently, a comprehensive qualitative–quantitative risk assessment was conducted to explore the impact of HESS design parameters, including storage size, pressure, flow rate, and temperature. Then, multi-objective optimization was performed considering the total environmental cost, total life cycle cost (TLCC), and risk cost index (RCI). The design of three green HESSs, gas hydrogen storage (GH2), liquid hydrogen storage (LH2), and material-based hydrogen storage (MH2), were compared. The results reveal that GH2 has the largest TLCC (568,164.60 USD/year), followed by MH2 (460,674.18 USD/year) and LH2 (383,895.25 USD/year) The RCI identifies LH2 (0.21) as the highest risk, primarily because of the potential explosion hazards. Although MH2 integration may offer cost and safety advantages, temperature control during hydrogen release poses challenges to its practical application. Thus, this study offers a balanced approach integrating safety and economic considerations for designing green HESSs, aiding decision-makers toward sustainable energy solutions.
KW - Hydrogen storage system
KW - Multi-criteria assessment
KW - Multi-objective optimization
KW - Safety-risk assessment
KW - Weather forecasting
UR - http://www.scopus.com/inward/record.url?scp=85192244922&partnerID=8YFLogxK
U2 - 10.1016/j.est.2024.111849
DO - 10.1016/j.est.2024.111849
M3 - Article
AN - SCOPUS:85192244922
SN - 2352-152X
VL - 90
JO - Journal of Energy Storage
JF - Journal of Energy Storage
M1 - 111849
ER -
