
AIMS Energy, 2015, 3(4): 505524. doi: 10.3934/energy.2015.4.505
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Optimal wind farm sitting using highresolution digital elevation models and randomized optimization
infoMETRICS L.t.d, Megalou Aleksandrou 20, Spata, Athens, PO 19004, Greece
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Special Issues: Remote sensing and Geoinformation Technology to Explore and Predict Renewable Energy Potential
References
1. S. CHOWDHURY, J. Z HANG, A. M ESSAC, AND L. CASTILLO, Exploring key factors influencing optimal farm design using mixeddiscrete particle swarm optimization, in 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, 2010.
2. S. CHOWDHURY, J. Z HANG, A. M ESSAC, AND L. CASTILLO, Unrestricted wind farm layout optimization (uwflo): Investigating key factors influencing the maximum power generation, Renewable Energy, 38 (2012), pp. 16–30.
3. C.R. CHU AND P.H. C HIANG, Turbulence effects on the wake flow and power production of a horizontalaxis wind turbine, Journal of Wind Engineering and Industrial Aerodynamics, 124(2014), pp. 82–89.
4. J. F ENG AND W. Z. SHEN, Wind farm layout optimization in complex terrain: A preliminary study on a gaussian hill, in Journal of Physics: Conference Series, vol. 524, IOP Publishing, 2014, p. 012146.
5. J. S. G ONZÁLEZ, M. B URGOS PAYAN, AND J. M. R IQUELME S ANTOS, Optimization of wind farm turbine layout including decision making under risk, Systems Journal, IEEE, 6 (2012), pp. 94–102.
6. J. S. G ONZÁLEZ, A. G. G. R ODRIGUEZ, J. C. M ORA, J. R. S ANTOS, AND M. B. PAYAN, Optimization of wind farm turbines layout using an evolutive algorithm, Renewable Energy, 35 (2010), pp. 1671–1681.
7. S. GRADY, M. H USSAINI, AND M. M. ABDULLAH, Placement of wind turbines using genetic algorithms, Renewable energy, 30 (2005), pp. 259–270.
8. H. GU AND J. WANG, Irregularshape wind farm micrositing optimization, Energy, 57 (2013), pp. 535–544.
9. N. HANSEN, The cma evolution strategy: a comparing review, in Towards a new evolutionary computation, Springer, 2006, pp. 75–102.
10. H.S. HUANG, Distributed genetic algorithm for optimization of wind farm annual profits, in Intelligent Systems Applications to Power Systems, 2007. ISAP 2007. International Conference on, IEEE, 2007, pp. 1–6.
11. T. JÄGER, R. M CKENNA, AND W. FICHTNER, Onshore wind energy in badenwürttemberg: a bottomup economic assessment of the sociotechnical potential.
12. N. O. JENSEN, A note on wind generator interaction, 1983.
13. I. K ATIC, J. H ØJSTRUP , AND N. JENSEN, A simple model for cluster efficiency, in European Wind Energy Association Conference and Exhibition, 1986, pp. 407–410.
14. K. KOUTROUMPAS, E. C INQUEMANI , P. KOURETAS, AND J. LYGEROS, Parameter identification for stochastic hybrid systems using randomized optimization: A case study on subtilin production by bacillus subtilis, Nonlinear Analysis: Hybrid Systems, 2 (2008), pp. 786–802.
15. K. KOUTROUMPAS, E. C INQUEMANI , AND J. LYGEROS, Randomized optimization methods in parameter identification for biochemical network models, Proceedings of FOSBE 2007, (2007).
16. X. LI , J. WANG, AND X. ZHANG, Equilateraltriangle mesh for optimal micrositing of wind farms, in Proceedings of the 14th WSEAS international conference on Computers, Corfu Island, Greece, 2010, pp. 23–25.
17. J. E. G. M ARTÍNEZ, Layout optimisation of offshore wind farms with realistic constraints and options, Master’s thesis, Delft University of Technology, 2014. Available:http://www.lr.tudelft.nl/fileadmin/Faculteit/LR/Organisatie/Afdelingen_en_Leerstoelen/Afdeling_AEWE/Wind_Energy/Education/Masters_Projects/Finished_Master_projects/doc/Julian_Gonzalez_r.pdf.
18. J. C. M ORA, J. M. C. B ARÓN, J. M. R. S ANTOS, AND M. B. PAYÁN, An evolutive algorithm for wind farm optimal design, Neurocomputing, 70 (2007), pp. 2651–2658.
19. G. MOSETTI, C. P OLONI, AND B. DIVIACCO, Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm, Journal of Wind Engineering and Industrial Aerodynamics, 51 (1994), pp. 105–116.
20. B. PÉREZ, R. M ÍNGUEZ , AND R. GUANCHE, Offshore wind farm layout optimization using mathematical programming techniques, Renewable Energy, 53 (2013), pp. 389–399.
21. E. S. POLITIS, J. P ROSPATHOPOULOS, D. C ABEZON, K. S. H ANSEN, P. C HAVIAROPOULOS, AND R. J. BARTHELMIE, Modeling wake effects in large wind farms in complex terrain: the problem, the methods and the issues, Wind Energy, 15 (2012), pp. 161–182.
22. P.E. R ÉTHORÉ, P. F UGLSANG, G. C. L ARSEN, T. B UHL, T. J. L ARSEN, H. A. M ADSEN, ET AL., Topfarm: Multifidelity optimization of offshore wind farm, Proceedings of the Twentyfirst, (2011), pp. 516–524.
23. R. A. RIVAS , J. C LAUSEN, K. S. H ANSEN, AND L. E. JENSEN, Solving the turbine positioning problem for large offshore wind farms by simulated annealing, Wind Engineering, 33 (2009), pp. 287–297.
24. S. M. F. RODRIGUES, P. B AUER, AND J. P IERIK, Modular approach for the optimal wind turbine micro siting problem through cmaes algorithm, in Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, ACM, 2013, pp. 1561–1568.
25. B. SAAVEDRAM ORENO, S. S ALCEDOS ANZ, A. PANIAGUAT INEO, L. P RIETO, AND A. PORTILLAFIGUERAS, Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms, Renewable Energy, 36 (2011), pp. 2838–2844.
26. M. SAMORANI, The wind farm layout optimization problem, in Handbook of Wind Power Systems, Springer, 2013, pp. 21–38.
27. S. ¸SI ¸SBOT , Ö. T URGUT, M. T UNÇ, AND Ü. ÇAMDALI, Optimal positioning of wind turbines on gökçeada using multiobjective genetic algorithm, Wind Energy, 13 (2010), pp. 297–306.
28. M. SONG, K. C HEN, Z. H E, AND X. ZHANG, Wake flow model of wind turbine using particle simulation, Renewable energy, 41 (2012), pp. 185–190.
29. M. SONG, K. C HEN, Z. H E, AND X. ZHANG, Bionic optimization for micrositing of wind farm on complex terrain, Renewable Energy, 50 (2013), pp. 551–557.
30. M. SONG, K. C HEN, Z. H E, AND X. ZHANG, Optimization of wind farm micrositing for complex terrain using greedy algorithm, Energy, 67 (2014), pp. 454–459.
31. J. T ZANOS, K. M ARGELLOS, AND J. LYGEROS, Optimal wind turbine placement via randomized optimization techniques, in Proceedings of the 17th Power Systems Computation Conference, Stockholm, Sweden, 2011, pp. 22–26.
32.M. WAGNER, K. V EERAMACHANENI, F. N EUMANN, AND U.M. OÂÂZREILLY, Optimizing the layout of 1000 wind turbines, European Wind Energy Association Annual Event, (2011), pp. 205–209.
33. C. A. WALFORD, Wind turbine reliability: understanding and minimizing wind turbine operation and maintenance costs, United States. Department of Energy, 2006.
34. C. WAN, J. WANG, G. YANG, X. L I , AND X. ZHANG, Optimal micrositing of wind turbines by genetic algorithms based on improved wind and turbine models, in Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on, IEEE, 2009, pp. 5092–5096.
35. C. WAN, J. WANG, G. YANG, AND X. ZHANG, Optimal micrositing of wind farms by particle swarm optimization, in Advances in swarm intelligence, Springer, 2010, pp. 198–205.
36. J. WANG, X. L I , AND X. ZHANG, Genetic optimal micrositing of wind farms by equilateraltriangle mesh, INTECH Open Access Publisher, 2011.
37. V. YAKHOT, S. O RSZAG, S. T HANGAM, T. G ATSKI, AND C. SPEZIALE, Development of turbulence models for shear flows by a double expansion technique, Physics of Fluids A: Fluid Dynamics (19891993), 4 (1992), pp. 1510–1520.
38. M. H. ZHANG, Wind Resource Assessment and Micrositing: Science and Engineering, Wiley, 2015.
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