S. Aghabozorgi, A. S. Shirkhorshidi, and T. Wah, Time-series clustering -A decade review, Information Systems, vol.53, pp.16-38, 2015.

T. Akhtar and C. A. Shoemaker, Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection, Journal of Global Optimization, vol.64, issue.1, pp.1573-2916, 2016.

B. Aksanli, J. Venkatesh, L. Zhang, and T. Rosing, Utilizing Green Energy Prediction to Schedule Mixed Batch and Service Jobs in Data Centers, SIGOPS Oper. Syst. Rev, vol.45, issue.3, pp.53-57, 2012.

A. and J. Cook, Modeling and enforcement of cloud computing service level agreements, 2012.

M. Alam, K. A. Shakil, and S. Sethi, Analysis and Clustering of Workload in Google Cluster Trace Based on Resource Usage, Proceedings of the 2016 IEEE Intl Conference on Computational Science and Engineering (CSE), pp.740-747, 2016.

E. Alsema, Energy Payback Time and CO2 Emissions of PV Systems, Practical Handbook of Photovoltaics, pp.1097-1117, 2012.

S. G. Anders, T. Andrae, and . Edler, On Global Electricity Usage of Communication Technology: Trends to 2030, Challenges, vol.6, issue.1, pp.117-157, 2015.

J. Antonanzas, N. Osorio, R. Escobar, R. Urraca, F. J. Martinez-de-pison et al., Review of photovoltaic power forecasting, Solar Energy, vol.136, pp.78-111, 2016.

M. Arlitt and T. Jin, A workload characterization study of the 1998 world cup web site, IEEE network, vol.14, issue.3, pp.30-37, 2000.

Y. M. Atwa, E. F. El-saadany, M. M. Salama, and R. Seethapathy, Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization, IEEE Transactions on Power Systems, vol.25, issue.1, pp.360-370, 2010.

A. Beloglazov, R. Buyya, A. Young-choon-lee, and . Zomaya, A taxonomy and survey of energy-efficient data centers and cloud computing systems, Advances in Computers, vol.82, pp.47-111, 2011.

A. Benoit and L. Lefèvre, Anne-Cécile Orgerie, and Issam Raïs. Shutdown Policies with Power Capping for Large Scale Computing Systems

T. F. Rivera, J. C. Pena, and . Cabaleiro, Lecture Notes in Computer Science, pp.134-146, 2017.

T. Benson, A. Akella, and D. A. Maltz, Network Traffic Characteristics of Data Centers in the Wild, Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement, IMC '10, pp.267-280, 2010.

P. E. Bett and H. E. Thornton, The climatological relationships between wind and solar energy supply in Britain, Renewable Energy, vol.87, pp.96-110, 2016.

K. Bilal, S. Ur-rehman, O. Malik, A. Khalid, E. Hameed et al., A taxonomy and survey on Green Data Center Networks, Future Generation Computer Systems, vol.36, pp.189-208, 2014.

M. G. Bosilovich, MERRA-2: File Specification, 2015.

E. P. George, G. M. Box, G. C. Jenkins, G. M. Reinsel, and . Ljung, Time Series Analysis: Forecasting and Control, 2015.

G. Bramerdorfer and A. Z?voianu, Surrogate-based multiobjective optimization of electrical machine designs facilitating tolerance analysis, IEEE Transactions on Magnetics, vol.53, issue.8, pp.1-11, 2017.

J. Branke, K. Deb, H. Dierolf, and M. Osswald, Finding Knees in Multi-objective Optimization

P. Rowe, A. Ti?o, and . Kabán, Parallel Problem Solving from Nature -PPSN VIII, Lecture Notes in Computer Science, pp.722-731, 2004.

M. Brown and J. Renau, Rerack: Power simulation for data centers with renewable energy generation, ACM SIGMETRICS Performance Evaluation Review, vol.39, issue.3, pp.77-81, 2011.

E. I. Alexander, J. R. Brownlee, J. Woodward, and . Swan, Metaheuristic Design Pattern: Surrogate Fitness Functions, Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

, Companion '15, pp.1261-1264, 2015.

R. N. Calheiros, R. Ranjan, A. Beloglazov, A. F. César, R. De-rose et al., CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, vol.41, pp.23-50, 2011.

, California GHG Emission Inventory Edition, 2016.

, California Independant System Operator

H. Casanova, Simgrid: A toolkit for the simulation of application scheduling, First IEEE/ACM International Symposium on Cluster Computing and the Grid, pp.430-437, 2001.

S. Caux, P. Renaud-goud, G. Rostirolla, and P. Stolf, IT Optimization for Datacenters Under Renewable Power Constraint, Parallel Processing, pp.339-351, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02305348

M. Ceraolo, New dynamical models of lead-acid batteries, IEEE transactions on Power Systems, vol.15, issue.4, pp.1184-1190, 2000.

F. K. Chan, A. W. Fu, and C. Yu, Haar wavelets for efficient similarity search of time-series: With and without time warping, IEEE Transactions on Knowledge and Data Engineering, vol.15, issue.3, pp.686-705, 2003.

K. Chan and A. Fu, Efficient time series matching by wavelets, Proceedings., 15th International Conference On, pp.126-133, 1999.

T. Muhammad-tayyab-chaudhry, A. Ling, . Manzoor, J. Syed-asad-hussain, and . Kim, Thermal-Aware Scheduling in Green Data Centers, ACM Comput. Surv, vol.47, issue.3, 2015.

C. Chen, S. Duan, T. Cai, and B. Liu, Online 24-h solar power forecasting based on weather type classification using artificial neural network, Solar Energy, vol.85, issue.11, pp.2856-2870, 2011.

K. H. Chen and Z. D. Ding, Lithium-ion battery lifespan estimation for hybrid electric vehicle, The 27th Chinese Control and Decision Conference, pp.5602-5605, 2015.

C. Chiasserini and R. R. Rao, Energy efficient battery management, IEEE journal on selected areas in communications, vol.19, issue.7, pp.1235-1245, 2001.

C. Chiasserini and R. R. Rao, Pulsed battery discharge in communication devices, Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, pp.88-95, 1999.

D. D. Chiras, Power from the Sun: A Practical Guide to Solar Electricity, 2013.

Y. Chu and P. Meisen, Review and comparison of different solar energy technologies. Global Energy Network Institute (GENI), 2011.

L. Cupertino, G. D. Costa, A. Oleksiak, W. Piatek, J. Pierson et al., Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results, Part B, vol.25, pp.535-553, 2015.

L. F. Cupertino, G. D. Costa, and J. Pierson, Towards a generic power estimator, Computer Science -Research and Development, vol.30, issue.2, pp.145-153, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01156610

C. Curry, Lithium-ion battery costs and market, Bloomberg New Energy Finance, issue.5, 2017.

G. Costa, L. Grange, and I. D. Courchelle, Modeling and generating large-scale Google-like workload, Seventh International Green and Sustainable Computing Conference (IGSC), pp.1-7, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01472021

L. Georges-da-costa, I. Grange, and . De-courchelle, Modeling, classifying and generating large-scale Google-like workload, Sustainable Computing: Informatics and Systems, vol.19, pp.305-314, 2018.

M. Dayarathna, Y. Wen, and R. Fan, Data Center Energy Consumption Modeling: A Survey, IEEE Communications Surveys Tutorials, vol.18, issue.1, pp.732-794, 2016.

T. Inès-de-courchelle, G. D. Guérout, T. Costa, Y. Monteil, and . Labit, Green energy efficient scheduling management. Simulation Modelling Practice and Theory, vol.93, pp.208-232, 2019.

K. Deb, Multi-objective optimization, Search Methodologies, pp.403-449, 2014.

K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE transactions on evolutionary computation, vol.6, issue.2, pp.182-197, 2002.

K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, Scalable test problems for evolutionary multiobjective optimization, Evolutionary Multiobjective Optimization, pp.105-145, 2005.

A. Dekka, R. Ghaffari, B. Venkatesh, and B. Wu, A survey on energy storage technologies in power systems, Electrical Power and Energy Conference (EPEC), pp.105-111, 2015.

R. Deng, Z. Yang, M. Chow, and J. Chen, A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches, IEEE Transactions on Industrial Informatics, vol.11, issue.3, pp.570-582, 2015.

W. Deng, F. Liu, H. Jin, and X. Liao, Online control of datacenter power supply under uncertain demand and renewable energy, 2013 IEEE International Conference on Communications (ICC), pp.4228-4232, 2013.

X. Deng, D. Wu, J. Shen, and J. He, Eco-Aware Online Power Management and Load Scheduling for Green Cloud Datacenters, IEEE Systems Journal, vol.10, issue.1, pp.78-87, 2016.

S. Di, D. Kondo, and W. Cirne, Characterization and Comparison of Cloud versus Grid Workloads, 2012 IEEE International Conference on Cluster Computing, pp.230-238, 2012.

S. Di, D. Kondo, and F. Cappello, Characterizing Cloud Applications on a Google Data Center, 2013 42nd International Conference on Parallel Processing, pp.468-473, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00936827

M. Diagne, M. David, P. Lauret, J. Boland, and N. Schmutz, Review of solar irradiance forecasting methods and a proposition for smallscale insular grids, Renewable and Sustainable Energy Reviews, vol.27, pp.65-76, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01090087

Z. Ding, L. Xie, Y. Lu, P. Wang, and S. Xia, Emission-Aware Stochastic Resource Planning Scheme for Data Center Microgrid Considering Batch Workload Scheduling and Risk Management, IEEE Transactions on Industry Applications, vol.54, issue.6, pp.5599-5608, 2018.

D. Dirnberger, Photovoltaic module measurement and characterization in the laboratory, pp.23-70, 2017.

C. Draxl, B. M. Hodge, A. Clifton, and J. Mccaa, Overview and Meteorological Validation of the Wind Integration National Dataset toolkit, 2015.

S. A. Dudani, The Distance-Weighted k-Nearest-Neighbor Rule, IEEE Transactions on Systems, Man, and Cybernetics, SMC, vol.6, issue.4, pp.325-327, 1976.

B. Dunn, H. Kamath, and J. Tarascon, Electrical Energy Storage for the Grid: A Battery of Choices, Science, vol.334, issue.6058, pp.1095-9203, 2011.

M. Ehrgott, Multicriteria Optimization, 2005.

L. Ager-wick-ellingsen, C. R. Hung, and A. , Hammer Strømman. Identifying key assumptions and differences in life cycle assessment studies of lithium-ion traction batteries with focus on greenhouse gas emissions, Transportation Research Part D: Transport and Environment, vol.55, pp.82-90, 2017.

I. Ben-elliston, M. Macgill, and . Diesendorf, Least cost 100% renewable electricity scenarios in the Australian National Electricity Market, Energy Policy, vol.59, pp.270-282, 2013.

N. A. Engerer and F. P. Mills, KPV: A clear-sky index for photovoltaics, Solar Energy, vol.105, pp.679-693, 2014.

X. Fan, W. Weber, and L. Barroso, Power Provisioning for a Warehouse-sized Computer, Proceedings of the 34th Annual International Symposium on Computer Architecture, ISCA '07, pp.13-23, 2007.

Y. Fan, Research on factors influencing an individual's behavior of energy management: A field study in China, Journal of Management Analytics, vol.4, issue.3, pp.203-239, 2017.

T. F. Fuller, M. Doyle, and J. Newman, Simulation and optimization of the dual lithium ion insertion cell, Journal of the Electrochemical Society, vol.141, issue.1, pp.1-10, 1994.

F. Gbaguidi, S. Boumerdassi, É. Renault, and E. Ezin, Characterizing servers workload in Cloud Datacenters, Future Internet of Things and Cloud (FiCloud), 2015 3rd International Conference On, pp.657-661, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01269580

M. Ghamkhari and H. Mohsenian-rad, Energy and Performance Management of Green Data Centers: A Profit Maximization Approach, IEEE Transactions on Smart Grid, vol.4, issue.2, pp.1017-1025, 2013.

K. Gillingham, D. Rapson, and G. Wagner, The Rebound Effect and Energy Efficiency Policy. Review of Environmental Economics and Policy, vol.10, issue.1, pp.68-88, 2016.

Í. Goiri, . Le, .. E. Md, R. Haque, T. D. Beauchea et al., GreenSlot : Scheduling Energy Consumption in Green Datacenters, Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, SC '11, vol.20, 2011.

Í. Goiri, W. Katsak, K. Le, T. D. Nguyen, and R. Bianchini, Parasol and GreenSwitch: Managing Datacenters Powered by Renewable Energy, Proceedings of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS '13, pp.51-64, 2013.

B. Goss, I. R. Cole, E. Koubli, D. Palmer, T. R. Betts et al., Modelling and prediction of PV module energy yield, pp.103-132, 2017.

L. Grange, P. Stolf, G. D. Costa, and A. Sayah, Heuristiques d'ordonnancement pour les centres de données alimentés par énergies renouvelables, Conférence d'informatique En Parallélisme, 2017.

L. Grange, G. D. Costa, and P. Stolf, Green IT scheduling for data center powered with renewable energy, Future Generation Computer Systems, vol.86, pp.99-120, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02319765

L. Grange, P. Stolf, G. D. Costa, and P. Renaud-goud, Cooperative and multi-objective power planning negotiation between datacenter and on-site renewable energy sources, 2018.

L. Grange, P. Stolf, G. D. Costa, and P. Renaud-goud, Négociation multiobjectif de profils de puissance de centre de données alimenté par énergies renouvelables sur site, Conférence d'informatique En Parallélisme, 2018.

L. Grange, P. Stolf, G. D. Costa, and P. Renaud-goud, Cooperative and Multi-Objective Power Planning Negotiation between Datacenter and on-Site Renewable Energy Sources, Submitted to IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2019.

C. Gu, L. Fan, W. Wu, H. Huang, and X. Jia, Greening cloud data centers in an economical way by energy trading with power grid, Future Generation Computer Systems, vol.78, pp.89-101, 2018.

W. Gu, Z. Sun, X. Wei, and H. Dai, A new method of accelerated life testing based on the Grey System Theory for a model-based lithium-ion battery life evaluation system, Journal of Power Sources, vol.267, pp.366-379, 2014.

T. Guérout, S. Medjiah, G. D. Costa, and T. Monteil, Quality of service modeling for green scheduling in Clouds, Sustainable Computing: Informatics and Systems, vol.4, pp.225-240, 2014.

C. W. Hansen and A. Pohl, Which models matter: Uncertainty and sensitivity analysis for photovoltaic power systems, IEEE 40th Photovoltaic Specialist Conference (PVSC), pp.175-0180, 2014.

H. Hao, Z. Mu, S. Jiang, Z. Liu, and F. Zhao, GHG Emissions from the Production of Lithium-Ion Batteries for Electric Vehicles in China, Sustainability, vol.9, issue.4, p.504, 2017.

M. Hicks, Clank: Architectural support for intermittent computation, 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA), pp.228-240, 2017.

K. Hinderer, U. Rieder, and M. Stieglitz, Dynamic Optimization: Deterministic and Stochastic Models, 2016.

A. Hooshmand, M. H. Poursaeidi, J. Mohammadpour, H. A. Malki, and K. Grigoriads, Stochastic model predictive control method for microgrid management, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), pp.1-7, 2012.

Y. Huang, S. Mao, and R. M. Nelms, Adaptive Electricity Scheduling in Microgrids, IEEE Transactions on Smart Grid, vol.5, issue.1, pp.270-281, 2014.

O. Illoh, S. Aghili, and S. Butakov, Using COBIT 5 for Risk to Develop Cloud Computing SLA Evaluation Templates, Service-Oriented Computing -ICSOC 2014 Workshops, pp.236-249, 2015.

, International Energy Agency. Key World Energy Statistics, 2018.

A. Iosup, H. Li, M. Jan, S. Anoep, C. Dumitrescu et al., The grid workloads archive, Future Generation Computer Systems, vol.24, issue.7, pp.672-686, 2008.

E. ?zgi, A. Öztopal, and B. Yerli, Short-mid-term solar power prediction by using artificial neural networks, Mustafa Kemal Kaymak, and Ahmet Duran ?ahin, vol.86, pp.725-733, 2012.

C. Jiang, Y. Wang, D. Ou, B. Luo, and W. Shi, Energy Proportional Servers: Where Are We in 2016, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pp.1649-1660, 2017.

A. Raúl, T. Jiménez, J. Serebrisky, and . Díaz, Power lost: Sizing electricity losses in transmission and distribution systems in Latin America and the Caribbean, 2014.

Y. Jin, A comprehensive survey of fitness approximation in evolutionary computation, Soft Computing, vol.9, issue.1, pp.3-12, 2005.

E. Jones, T. Oliphant, and P. Peterson, Open source scientific tools for Python, 2001.

M. R. Jongerden and B. R. Haverkort, Battery Modeling. Info:Eu

, Repo/Semantics/Report TR-CTI, Centre for Telematics and Information Technology, 2008.

R. Marijn, B. R. Jongerden, and . Haverkort, Battery Aging, Battery Charging and the Kinetic Battery Model: A First Exploration, Quantitative Evaluation of Systems, pp.88-103, 2017.

A. Kamjoo, A. Maheri, A. M. Dizqah, and G. A. Putrus, Multiobjective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming, International Journal of Electrical Power & Energy Systems, vol.74, pp.187-194, 2016.

K. Marios, K. C. Karakasis, and . Giannakoglou, On the use of metamodelassisted, multi-objective evolutionary algorithms. Engineering Optimization, vol.38, pp.941-957, 2006.

P. Deepak-paramashivan-kaundinya, N. H. Balachandra, and . Ravindranath, Gridconnected versus stand-alone energy systems for decentralized power-A review of literature, Renewable and Sustainable Energy Reviews, vol.13, issue.8, pp.2041-2050, 2009.

S. Kavulya, J. Tan, R. Gandhi, and P. Narasimhan, An Analysis of Traces from a Production MapReduce Cluster, 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), pp.94-103, 2010.

A. Khosravi, A. N. Toosi, and R. Buyya, Online virtual machine migration for renewable energy usage maximization in geographically distributed cloud data centers. Concurrency and Computation: Practice and Experience, page 0, 2017.

J. Kim, M. Ruggiero, D. Atienza, and M. Lederberger, Correlation-aware Virtual Machine Allocation for Energy-efficient Datacenters, Proceedings of the Conference on Design, Automation and Test in Europe, DATE '13, pp.1345-1350, 2013.

G. T. Klise and J. S. Stein, Models used to assess the performance of photovoltaic systems, 2009.

J. Mykel and . Kochenderfer, Decision Making under Uncertainty: Theory and Application. Lincoln Laboratory Series, 2015.

F. Kong and X. Liu, A Survey on Green-Energy-Aware Power Management for Datacenters, ACM Computing Surveys, vol.47, issue.2, pp.1-38, 2014.

V. Kostylev and A. Pavlovski, Solar power forecasting performance-towards industry standards, 1st International Workshop on the Integration of Solar Power into Power Systems, 2011.

V. Krakowski, E. Assoumou, V. Mazauric, and N. Maïzi, Reprint of Feasible path toward 40-100% renewable energy shares for power supply in France by 2050: A prospective analysis, Applied Energy, vol.184, pp.1529-1550, 2016.

K. Kritikos, B. Pernici, P. Plebani, C. Cappiello, M. Comuzzi et al., A Survey on Service Quality Description. ACM Comput. Surv, vol.46, issue.1, 2013.

K. , P. Kumar, and B. Saravanan, Recent techniques to model uncertainties in power generation from renewable energy sources and loads in microgrids -A review, Renewable and Sustainable Energy Reviews, vol.71, pp.348-358, 2017.

N. Kumar, G. S. Aujla, S. Garg, K. Kaur, R. Ranjan et al., Renewable Energy-Based Multi-Indexed Job Classification and Container Management Scheme for Sustainability of Cloud Data Centers, IEEE Transactions on Industrial Informatics, vol.15, issue.5, pp.2947-2957, 2019.

K. Kurowski, A. Oleksiak, W. Pi?tek, T. Piontek, A. Przybyszewski et al., DCworms -A tool for simulation of energy efficiency in distributed computing infrastructures, Simulation Modelling Practice and Theory, vol.39, pp.135-151, 2013.

J. H. Lee, Energy supply planning and supply chain optimization under uncertainty, Journal of Process Control, vol.24, issue.2, pp.323-331, 2014.

H. Lei, T. Zhang, Y. Liu, Y. Zha, and X. Zhu, SGEESS: Smart green energy-efficient scheduling strategy with dynamic electricity price for data center, Journal of Systems and Software, vol.108, pp.23-38, 2015.

H. Lei, R. Wang, T. Zhang, Y. Liu, and Y. Zha, A multi-objective co-evolutionary algorithm for energy-efficient scheduling on a green data center, Computers & Operations Research, vol.75, pp.103-117, 2016.

C. Li, R. Wang, T. Li, D. Qian, and J. Yuan, Managing Green Datacenters Powered by Hybrid Renewable Energy Systems, 11th International Conference on Autonomic Computing ({ICAC} 14), pp.261-272, 2014.

S. Li, D. C. Wunsch, E. A. O'hair, and M. G. Giesselmann, Using neural networks to estimate wind turbine power generation, IEEE Transactions on Energy Conversion, vol.16, issue.3, pp.276-282, 2001.

X. Li, X. Jiang, P. Garraghan, and Z. Wu, Holistic energy and failure aware workload scheduling in Cloud datacenters, Future Generation Computer Systems, vol.78, pp.887-900, 2018.

Y. Li, A. C. Orgerie, and J. M. Menaud, Opportunistic Scheduling in Clouds Partially Powered by Green Energy, 2015 IEEE International Conference on Data Science and Data Intensive Systems, pp.448-455, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01205911

Y. Li, A. C. Orgerie, and J. M. Menaud, Balancing the Use of Batteries and Opportunistic Scheduling Policies for Maximizing Renewable Energy Consumption in a Cloud Data Center, 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp.408-415, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01432752

Y. Li, X. Wang, P. Luo, and Q. Pan, Thermal-Aware Hybrid Workload Management in a Green Datacenter towards Renewable Energy Utilization, Energies, vol.12, issue.8, p.1494, 2019.

Z. Li, J. Ge, C. Li, H. Yang, H. Hu et al., Energy cost minimization with job security guarantee in Internet data center, Future Generation Computer Systems, vol.73, pp.63-78, 2017.

H. Liang and W. Zhuang, Stochastic Modeling and Optimization in a Microgrid: A, Survey. Energies, vol.7, issue.4, pp.2027-2050, 2014.

A. Liefooghe, M. Basseur, J. Humeau, L. Jourdan, and E. Talbi, On optimizing a bi-objective flowshop scheduling problem in an uncertain environment, Computers & Mathematics with Applications, vol.64, issue.12, pp.3747-3762, 2012.

B. Liu, Y. Lin, and Y. Chen, Quantitative workload analysis and prediction using Google cluster traces, Computer Communications Workshops (INFOCOM WKSHPS), 2016 IEEE Conference On, pp.935-940, 2016.

C. Dong, J. Liu, and . Nocedal, On the limited memory BFGS method for large scale optimization, Mathematical Programming, vol.45, issue.1, pp.503-528, 1989.

L. Liu, A. Chattopadhyay, and U. Mitra, Exploiting policy structure for solving MDPs with large state space, 2018 52nd Annual Conference on Information Sciences and Systems (CISS), pp.1-6, 2018.

X. Liu, P. Liu, H. Li, Z. Li, C. Zou et al., Energy-aware Task Scheduling Strategies with QoS Constraint for Green Computing in Cloud Data Centers, Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems, RACS '18, pp.260-267, 2018.

Z. Liu and S. Cho, Characterizing Machines and Workloads on a Google Cluster, 2012 41st International Conference on Parallel Processing Workshops, pp.397-403, 2012.

Z. Liu, A. Wierman, Y. Chen, B. Razon, and N. Chen, Data center demand response: Avoiding the coincident peak via workload shifting and local generation, Performance Evaluation, vol.70, issue.10, pp.770-791, 2013.

Z. Liu, I. Liu, S. Low, and A. Wierman, Pricing Data Center Demand Response, The 2014 ACM International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS '14, pp.111-123, 2014.

T. Logenthiran, D. Srinivasan, A. M. Khambadkone, and H. N. Aung, Multi-Agent System (MAS) for short-term generation scheduling of a microgrid, 2010 IEEE International Conference on Sustainable Energy Technologies (ICSET), pp.1-6, 2010.

E. Lorenz, J. Hurka, D. Heinemann, and H. G. Beyer, Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.2, issue.1, pp.2-10, 2009.

P. Manganiello, M. Balato, and M. Vitelli, A Survey on Mismatching and Aging of PV Modules: The Closed Loop, IEEE Transactions on Industrial Electronics, vol.62, issue.11, pp.7276-7286, 2015.

F. James, J. G. Manwell, and . Mcgowan, Lead acid battery storage model for hybrid energy systems, Solar Energy, vol.50, issue.5, pp.90060-90062, 1993.

, Comparison of predictive models for photovoltaic module performance, 33rd IEEE Photovoltaic Specialists Conference, pp.1-6, 2008.

R. , T. Marler, and J. S. Arora, The weighted sum method for multiobjective optimization: New insights. Structural and multidisciplinary optimization, vol.41, pp.853-862, 2010.

R. T. Marler and J. S. Arora, Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, vol.26, pp.369-395, 2004.

S. Z. Martínez and C. A. Coello, Combining surrogate models and local search for dealing with expensive multi-objective optimization problems, IEEE Congress on Evolutionary Computation, pp.2572-2579, 2013.

C. Marty and R. Philipona, The clear-sky index to separate clear-sky from cloudy-sky situations in climate research, Geophysical Research Letters, vol.27, issue.17, pp.2649-2652, 2000.

D. F. Menicucci, PVFORM -a new approach to photovoltaic system performance modeling, 1985.

J. Miller, L. Bird, J. Heeter, and B. Gorham, Renewable Electricity Use by the U.S. Information and Communication Technology (ICT) Industry, 2015.

I. S. Moreno, P. Garraghan, P. Townend, and J. Xu, Analysis, Modeling and Simulation of Workload Patterns in a Large-Scale Utility Cloud, IEEE Transactions on Cloud Computing, vol.2, issue.2, pp.208-221, 2014.

A. Murata, H. Ohtake, and T. Oozeki, Modeling of uncertainty of solar irradiance forecasts on numerical weather predictions with the estimation of multiple confidence intervals, Renewable Energy, vol.117, pp.193-201, 2018.

, Solar Power Data for Integration Studies, 2012.

N. Nikmehr, S. Najafi-ravadanegh, and A. Khodaei, Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty, Applied Energy, vol.198, pp.267-279, 2017.

T. Okabe, Y. Jin, and B. Sendhoff, A critical survey of performance indices for multi-objective optimisation, The 2003 Congress on Evolutionary Computation, 2003. CEC '03, vol.2, pp.878-885, 2003.

A. C. Orgerie, L. Lefèvre, and J. P. Gelas, Demystifying energy consumption in Grids and Clouds, Green Computing Conference, 2010 International, pp.335-342, 2010.
URL : https://hal.archives-ouvertes.fr/ensl-00527642

A. Pahlevan, M. Rossi, P. G. Valle, D. Brunelli, and D. Atienza, Joint Computing and Electric Systems Optimization for Green Datacenters, Handbook of Hardware/Software Codesign, pp.1163-1183, 2017.

G. Parise and L. Parise, Electrical Distribution for a Reliable Data Center, IEEE Transactions on Industry Applications, vol.49, issue.4, pp.1697-1702, 2013.

D. Paul, W. Zhong, and S. K. Bose, Demand Response in Data Centers Through Energy-Efficient Scheduling and Simple Incentivization, IEEE Systems Journal, vol.11, issue.2, pp.613-624, 2017.

J. Peng, L. Lu, and H. Yang, Review on life cycle assessment of energy payback and greenhouse gas emission of solar photovoltaic systems, Renewable and Sustainable Energy Reviews, vol.19, pp.255-274, 2013.

J. Pierson, G. Baudic, S. Caux, B. Celik, G. D. Costa et al., DATAZERO: Datacenter With Zero Emission and Robust Management Using Renewable Energy, IEEE Access, vol.7, pp.103209-103230, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02370962

A. Poullikkas, A comparative overview of large-scale battery systems for electricity storage, Renewable and Sustainable Energy Reviews, vol.27, pp.778-788, 2013.

B. Warren and . Powell, Approximate Dynamic Programming: Solving the Curses of Dimensionality, 2011.

, Markov Decision Processes. Wiley Series in Probability and Statistics, 1994.

L. Radu, Determinants of Green ICT Adoption in Organizations: A Theoretical Perspective, Sustainability, vol.8, issue.8, p.731, 2016.

A. Rahmoun and H. Biechl, Modelling of Li-ion batteries using equivalent circuit diagrams. Electrical review, ISSN, pp.33-2097, 2012.

P. Parthasarathy-ranganathan, D. Leech, J. Irwin, and . Chase, Ensemblelevel Power Management for Dense Blade Servers, Proceedings of the 33rd Annual International Symposium on Computer Architecture, ISCA '06, pp.66-77, 2006.

V. Rao, G. Singhal, A. Kumar, and N. Navet, Battery model for embedded systems, 18th International Conference on VLSI Design Held Jointly with 4th International Conference on Embedded Systems Design, pp.105-110, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00099956

R. G. Regis, Evolutionary Programming for High-Dimensional Constrained Expensive Black-Box Optimization Using Radial Basis Functions, IEEE Transactions on Evolutionary Computation, vol.18, issue.3, pp.326-347, 2014.

C. Reiss, J. Wilkes, and J. L. Hellerstein, Google cluster-usage traces: Format+ schema, pp.1-14, 2011.

C. Reiss, A. Tumanov, R. Gregory, R. H. Ganger, M. Katz et al., Heterogeneity and dynamicity of clouds at scale: Google trace analysis, Proceedings of the Third ACM Symposium on Cloud Computing, 2012.

C. Reiss, A. Tumanov, G. R. Ganger, Y. H. Katz, and M. A. Kozuch, Towards Understanding Heterogeneous Clouds at Scale: Google Trace Analysis, 2012.

N. Riquelme, C. Von-lücken, and B. Baran, Performance metrics in multi-objective optimization, Computing Conference (CLEI), pp.1-11, 2015.

G. Rostirolla, Scheduling in Cloud Data Center Powered by Renewable Energy Only With Mixed Phases-Based Workload, 2019.

G. Rostirolla, L. Grange, M. Thi, P. Stolf, J. Pierson et al., Sizing and Management of Energy Sources for Green Datacenters with Renewable Energy, Stéphane Caux, and Jérôme Lecuivre, 2019.

V. Nikolaos and . Sahinidis, Optimization under uncertainty: State-of-the-art and opportunities, Computers & Chemical Engineering, vol.28, issue.6, pp.971-983, 2004.

N. Schilling, M. Wistuba, L. Drumond, and L. Schmidt-thieme, Hyperparameter Optimization with Factorized Multilayer Perceptrons, Machine Learning and Knowledge Discovery in Databases, pp.87-103, 2015.

M. Sengupta, Y. Xie, A. Lopez, A. Habte, G. Maclaurin et al., The National Solar Radiation Data Base (NSRDB), vol.89, pp.51-60, 2018.

S. Shan and G. Wang, Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive blackbox functions. Structural and Multidisciplinary Optimization, vol.41, pp.1615-1488, 2010.

N. Sharma, S. Barker, D. Irwin, and P. Shenoy, Blink: Managing Server Clusters on Intermittent Power, Proceedings of the Sixteenth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS XVI, pp.185-198, 2011.

L. Shi and K. Rasheed, A Survey of Fitness Approximation Methods Applied in Evolutionary Algorithms, Computational Intelligence in Expensive Optimization Problems, Adaptation Learning and Optimization, pp.3-28, 2010.

W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu, Edge Computing: Vision and Challenges, IEEE Internet of Things Journal, vol.3, issue.5, pp.637-646, 2016.

J. Shuja, A. Gani, S. Shamshirband, R. Ahmad, and K. Bilal, Sustainable cloud data centers: A survey of enabling techniques and technologies, Renewable and Sustainable Energy Reviews, vol.62, pp.195-214, 2016.

P. Siano, Demand response and smart grids-A survey, Renewable and Sustainable Energy Reviews, vol.30, pp.461-478, 2014.

G. Sideratos and N. D. Hatziargyriou, An Advanced Statistical Method for Wind Power Forecasting, IEEE Transactions on Power Systems, vol.22, issue.1, pp.258-265, 2007.

S. Radomir, B. J. Stankovi?, and . Falkowski, The Haar wavelet transform: Its status and achievements, Computers & Electrical Engineering, vol.29, issue.1, pp.25-44, 2003.

N. Bruce and . Stram, Key challenges to expanding renewable energy, Energy Policy, vol.96, pp.728-734, 2016.

F. Strunk, An Analysis of Linux Boot Times, 2008.

H. Sun, P. Stolf, J. Pierson, and G. Costa, Energyefficient and thermal-aware resource management for heterogeneous datacenters, Sustainable Computing: Informatics and Systems, vol.4, pp.292-306, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01153804

H. Sun, P. Stolf, and J. Pierson, Spatio-temporal thermalaware scheduling for homogeneous high-performance computing datacenters, Future Generation Computer Systems, vol.71, pp.157-170, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01740033

S. Talari, M. Yazdaninejad, and M. Haghifam, Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads, Transmission Distribution IET Generation, vol.9, issue.12, pp.1498-1509, 2015.

R. Tibshirani, G. Walther, and T. Hastie, Estimating the number of clusters in a data set via the gap statistic, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.411-423, 2001.

J. D. Ullman, NP-complete scheduling problems, Journal of Computer and System Sciences, vol.10, issue.3, pp.384-393, 1975.

G. Urdaneta, G. Pierre, and M. Van-steen, Wikipedia workload analysis for decentralized hosting, Computer Networks, vol.53, issue.11, pp.1830-1845, 2009.

P. Van-den-bossche, F. Vergels, J. Van-mierlo, J. Matheys, and W. Van-autenboer, SUBAT: An assessment of sustainable battery technology, Journal of Power Sources, vol.162, issue.2, pp.913-919, 2006.

W. Van-heddeghem, S. Lambert, B. Lannoo, D. Colle, M. Pickavet et al., Trends in worldwide ICT electricity consumption from, Computer Communications, vol.50, pp.64-76, 2007.

J. Van-mierlo, P. Van-den-bossche, and G. Maggetto, Models of energy sources for EV and HEV: Fuel cells, batteries, ultracapacitors, flywheels and enginegenerators, Journal of Power Sources, vol.128, issue.1, pp.76-89, 2004.

K. Van-moffaert, M. M. Drugan, and A. Nowé, Hypervolume-Based Multi-Objective Reinforcement Learning, Evolutionary Multi-Criterion Optimization, pp.352-366, 2013.

D. A. Van-veldhuizen and G. B. Lamont, Evolutionary computation and convergence to a pareto front, Late Breaking Papers at the Genetic Programming 1998 Conference, pp.221-228, 1998.

V. Villebonnet, G. D. Costa, L. Lefevre, J. M. Pierson, and P. Stolf, Dynamically Building Energy Proportional Data Centers with Heterogeneous Computing Resources, 2016 IEEE International Conference on Cluster Computing (CLUS-TER), pp.217-220, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01346600

V. Villebonnet, G. Costa, L. Lefevre, J. M. Pierson, and P. Stolf, Energy Aware Dynamic Provisioning for Heterogeneous Data Centers, 28th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pp.206-213, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01355452

G. Laszewski, L. Wang, A. J. Younge, and X. He, Power-aware scheduling of virtual machines in DVFS-enabled clusters, 2009 IEEE International Conference on Cluster Computing and Workshops, pp.1-10, 2009.

H. Wang, M. Olhofer, and Y. Jin, A mini-review on preference modeling and articulation in multi-objective optimization: Current status and challenges, Complex & Intelligent Systems, vol.3, issue.4, pp.233-245, 2017.

L. Wang, G. Laszewski, J. Dayal, and F. Wang, Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS, 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CC-Grid), pp.368-377, 2010.

W. Wang and M. Sebag, Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search, Machine Learning, vol.92, pp.403-429, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00852048

M. Weiss, J. Haufe, M. Carus, M. Brandão, S. Bringezu et al., A Review of the Environmental Impacts of Biobased Materials, Journal of Industrial Ecology, vol.16, issue.s1, pp.169-181, 2012.

X. Wu, X. Wang, and C. Qu, A Hierarchical Framework for Generation Scheduling of Microgrids, IEEE Transactions on Power Delivery, vol.29, issue.6, pp.2448-2457, 2014.

A. A. Zainelabden, A. Ibrahim, D. Kliazovich, and P. Bouvry, On Service Level Agreement Assurance in Cloud Computing Data Centers, 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), pp.921-926, 2016.

H. Zhang, S. Shao, H. Xu, H. Zou, and C. Tian, Free cooling of data centers: A review, Renewable and Sustainable Energy Reviews, vol.35, pp.171-182, 2014.

A. Zhou, B. Qu, H. Li, and S. Zhao, Multiobjective evolutionary algorithms: A survey of the state of the art, Ponnuthurai Nagaratnam Suganthan, and Qingfu Zhang, vol.1, pp.32-49, 2011.

W. Zhou, H. Yang, and Z. Fang, A novel model for photovoltaic array performance prediction, Applied Energy, vol.84, issue.12, pp.1187-1198, 2007.

Z. Zhou, J. Abawajy, M. Chowdhury, Z. Hu, K. Li et al., Minimizing SLA violation and power consumption in Cloud data centers using adaptive energy-aware algorithms. Future Generation Computer Systems, 2017.

Z. Zhu, J. Tang, S. Lambotharan, W. Hau-chin, and Z. Fan, An integer linear programming based optimization for home demand-side management in smart grid, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), pp.1-5, 2012.

E. Zitzler and L. Thiele, Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach, IEEE Transactions on Evolutionary Computation, vol.3, issue.4, pp.257-271, 1999.

E. Zitzler, K. Deb, and L. Thiele, Comparison of multiobjective evolutionary algorithms: Empirical results, Evolutionary computation, vol.8, issue.2, pp.173-195, 2000.

E. Zitzler, M. Laumanns, and L. Thiele, Improving the Strength Pareto Evolutionary Algorithm. TIK-report, 2001.