T. Tezer, R. Yaman, and G. Yaman, Evaluation of approaches used for optimization of stand-alone hybrid renewable 2 energy systems, Renewable and Sustainable Energy Reviews, vol.73, pp.840-53, 2017.

B. Guinot, B. Champel, F. Montignac, E. Lemaire, D. Vannucci et al., Techno-economic study of a PV-4 hydrogen-battery hybrid system for off-grid power supply: Impact of performances' ageing on optimal system 5 sizing and competitiveness, International Journal of Hydrogen Energy, vol.40, issue.6, pp.623-655, 2015.

B. Guinot, Y. Bultel, F. Montignac, D. Riu, E. Pinton et al., Economic impact of performances 8 degradation on the competitiveness of energy storage technologies -Part 1: Introduction to the simulation-9 optimization platform ODYSSEY and elements of validation on a PV-hydrogen hybrid system, International 10 Journal of Hydrogen Energy, vol.38, pp.15219-15251, 2013.

B. Guinot, Y. Bultel, F. Montignac, D. Riu, N. Borgne et al., Economic impact of performances degradation on the 12 competitiveness of energy storage technologies -Part 2: Application on an example of PV production guarantee, International Journal of Hydrogen Energy, vol.13, pp.13702-13718, 2013.

G. Mavrotas, K. Florios, and D. Vlachou, Energy planning of a hospital using Mathematical Programming and Monte 15

, Carlo simulation for dealing with uncertainty in the economic parameters, Energy Conversion and Management, vol.16, pp.722-753, 2010.

G. Mavromatidis, K. Orehounig, and J. Carmeliet, A review of uncertainty characterisation approaches for the optimal 18 design of distributed energy systems, Renewable and Sustainable Energy Reviews, vol.88, pp.258-77, 2018.

R. Dufo-lópez, E. Pérez-cebollada, J. L. Bernal-agustín, and I. Martínez-ruiz, Optimisation of energy supply at off-grid 21 healthcare facilities using Monte Carlo simulation, Energy Conversion and Management, vol.113, pp.321-351, 2016.

Y. Zheng, B. M. Jenkins, K. Kornbluth, and C. Traeholt, Optimization under uncertainty of a biomass-integrated renewable 24 energy microgrid with energy storage, Renewable Energy, vol.123, pp.204-221, 2018.

R. Dufo-lópez, L. A. Fernández-jiménez, I. J. Ramírez-rosado, J. S. Artal-sevil, and J. A. Domínguez-navarro, , p.26

J. L. Agustín, Daily operation optimisation of hybrid stand-alone system by model predictive control considering 27 ageing model, Energy Conversion and Management, vol.134, pp.167-77, 2017.

S. Moret, C. Gironès, V. Bierlaire, M. Maréchal, and F. , Characterization of input uncertainties in strategic energy 29 planning models, Applied Energy, vol.202, pp.597-617, 2017.

P. Gabrielli, F. Fürer, G. Mavromatidis, and M. Mazzotti, Robust and optimal design of multi-energy systems with 31 seasonal storage through uncertainty analysis, Applied Energy, vol.238, 2019.

L. Bertuccioli, A. Chan, D. Hart, F. Lehner, B. Madden et al., , p.34

, European Union. E4tech Sàrl and Element Energy Ltd, 2014.

Ø. Ulleberg, The importance of control strategies in PV-hydrogen systems, Solar Energy, vol.76, pp.323-332, 2004.

R. Carapellucci and L. Giordano, Modeling and optimization of an energy generation island based on renewable 38 technologies and hydrogen storage systems, International Journal of Hydrogen Energy, vol.37, pp.2081-93, 2012.

E. Dursun and O. Kilic, Comparative evaluation of different power management strategies of a stand-alone 41

. Pv/wind, PEMFC hybrid power system, International Journal of Electrical Power & Energy Systems, vol.34, pp.81-123, 2012.

E. Zitzler, M. Laumanns, and L. Thiele, SPEA2: Improving the strength pareto evolutionary algorithm, Eidgenössische, vol.44

Z. Technische-hochschule, Institut für Technische Informatik und Kommunikationsnetze (TIK), p.45, 2001.

Y. Kalinci, A. Hepbasli, and I. Dincer, Techno-economic analysis of a stand-alone hybrid renewable energy system with 47 hydrogen production and storage options, International Journal of Hydrogen Energy, vol.40, pp.7652-64, 2015.

H. Meschede, H. Dunkelberg, F. Stöhr, R. H. Peesel, and J. Hesselbach, Assessment of probabilistic distributed factors 50 influencing renewable energy supply for hotels using Monte-Carlo methods, Energy (Oxford), vol.128, pp.86-100, 2017.

A. Saltelli, S. Tarantola, F. Campolongo, and M. Ratto, Sensitivity Analysis in Practice: A Guide to Assessing Scientific 52

. Models, , 2004.

J. J. Roberts, M. Cassula, A. Silveira, J. L. Da, C. Bortoni et al., Robust multi-objective optimization 54 of a renewable based hybrid power system, Applied Energy, vol.223, pp.52-68, 2018.

G. Mavromatidis, K. Orehounig, and J. Carmeliet, Uncertainty and global sensitivity analysis for the optimal design of 56 distributed energy systems, Applied Energy, vol.214, pp.219-257, 2018.

S. Moret, Strategic energy planning under uncertainty, vol.58, 2017.

A. Bouloré, C. Struzik, and F. Gaudier, Uncertainty and sensitivity analysis of the nuclear fuel thermal behavior, Nuclear 60 Engineering and Design, vol.253, pp.200-210, 2012.

E. Borgonovo and E. Plischke, Sensitivity analysis: A review of recent advances, European Journal of Operational 1 Research, vol.248, pp.869-87, 2016.

E. A. Groen, E. Bokkers, R. Heijungs, and I. De-boer, Methods for global sensitivity analysis in life cycle 3 assessment, Int J Life Cycle Assess, vol.22, pp.1125-1162, 2017.

W. Tian, A review of sensitivity analysis methods in building energy analysis, Renewable and Sustainable Energy 5 Reviews, vol.20, pp.411-420, 2013.

F. Campolongo, S. Tarantola, and A. Saltelli, Tackling quantitatively large dimensionality problems, Computer Physics, vol.7, pp.75-85, 1999.

M. D. Morris, Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, vol.33, pp.161-170, 1991.

&. Sobol, . Im, S. Tarantola, D. Gatelli, S. S. Kucherenko et al., Estimating the approximation error when fixing 11 unessential factors in global sensitivity analysis, Reliability Engineering & System Safety, vol.92, 2007.

I. M. Sobol, Sensitivity estimates for non linear mathematical models, 1993.

T. Homma and A. Saltelli, Importance measures in global sensitivity analysis of nonlinear models, Reliability 15 Engineering and System Safety, vol.52, pp.2-6, 1996.

A. Saltelli, Making best use of model evaluations to compute sensitivity indices, Computer Physics Communications, vol.17, pp.280-97, 2002.

A. Zakariazadeh, S. Jadid, and P. Siano, Stochastic operational scheduling of smart distribution system considering wind 19 generation and demand response programs, International Journal of Electrical Power & Energy Systems, vol.20, pp.218-243, 2014.

S. Pazouki and M. Haghifam, Optimal planning and scheduling of energy hub in presence of wind, storage and 22 demand response under uncertainty, International Journal of Electrical Power & Energy Systems, vol.80, issue.23, pp.219-258, 2016.

G. Mavromatidis, K. Orehounig, and J. Carmeliet, Design of distributed energy systems under uncertainty: A two-stage 25 stochastic programming approach, Applied Energy, vol.222, pp.932-50, 2018.

D. Bertsimas and M. Sim, The Price of Robustness, Oper Res, vol.52, p.27, 2004.

S. Moret, M. Bierlaire, and F. Maréchal, Robust optimization for strategic energy planning, Informatica, vol.27, pp.625-673, 2016.

F. Maggioni, F. A. Potra, and M. Bertocchi, A scenario-based framework for supply planning under uncertainty: stochastic 30 programming versus robust optimization approaches, Comput Manag Sci, vol.14, pp.5-44, 2017.

A. Maleki, M. G. Khajeh, and M. Ameri, Optimal sizing of a grid independent hybrid renewable energy system 33 incorporating resource uncertainty, and load uncertainty, International Journal of Electrical Power & Energy 34 Systems, vol.83, pp.514-538, 2016.

M. Cantoni, M. Marseguerra, and E. Zio, Genetic algorithms and Monte Carlo simulation for optimal plant design

, Reliability Engineering & System Safety, vol.68, pp.29-38, 2000.

M. Marseguerra, E. Zio, and L. Podofillini, Genetic Algorithms and Monte Carlo Simulation for the Optimization of 38

, /paper/Genetic-Algorithms-and-Monte-Carlo-Simulation-for-39, 2007.

. Marseguerra-zio, , vol.33229, 2018.

, The Power to Change: Solar and Wind Cost Reduction Potential to 2025. IRENA, 2016.

S. Weckend, A. Wade, and G. Heath, End-of-Life Management: Solar Photovoltaic Panels

, Energy Agency and International Energy Agency Photovoltaic Power Systems, 2016.

G. Saur, J. M. Kurtz, H. N. Dinh, C. D. Ainscough, and S. Onorato, State-of-the-Art Fuel Cell Voltage Durability and Cost 44 Status: 2018 Composite Data Products

, , vol.45, p.2018

C. Chardonnet, D. Vos, L. Genoese, F. Roig, G. Bart et al., Study on early business cases for H2 in 47 energy storage and more broadly power to H2 applications, 2017.

B. Battke, T. S. Schmidt, D. Grosspietsch, and V. H. Hoffmann, A review and probabilistic model of lifecycle costs of 49 stationary batteries in multiple applications, Renewable and Sustainable Energy Reviews, vol.25, 2013.

, Electricity Storage and Renewables: Costs and Markets to 2030, 2017.

Y. Riffonneau, F. Barruel, and S. Bacha, Problématique du stockage associé aux systèmes photovoltaïques connectés au 53 réseau. Conférence Internationale sur Les Energies Renouvelables ICRE'07, 2007.