Mehran University Research Journal Of Engineering &
Technology (HEC Recognized In Category "X")
Publishing Since 1982.



For Authors
For Readers
Article Information  
A New Hybrid Metaheuristic Algorithm for Wind Farm Micrositing

Keywords: Wind Farm, Jensen Wake Model, Nature Inspired Algorithms, Differential Evolution Algorithm, Firefly algorithm, Genetic Algorithm, Hybrid Meta-Heuristic Algorithm

Mehran University Research Journal of Engineering & Technology

Volume 36 ,  Issue 3

SHAFIQ-UR-REHMAN   MASSAN , ASIM IMDAD WAGAN   , MUHAMMAD MUJTABA SHAIKH   ,

References
1. Massan, S.-R., Wagan, A.I., Shaikh, M.M., and Abro, R., "Wind Turbine Micrositing by Using the Firefly Algorithm",Applied Soft Computing, Volume 27, pp. 450-456, November, 2015.
2. Rajper, S., and Amin, I.J., "Optimization of Wind Turbine Micrositing: A Comparative Study", Renewable and Sustainable Energy Reviews, Volume 16, pp. 5485-5492, 2012.
3. Mittal, A., "Optimization of the Layout of Large Wind Farms using Genetic Algorithm", MS Thesis, Department of Aerospace and Mechanical Engineering, Case Western Reserve University, USA, 2010.
4. Wan, C., Wang, J., Yang, G., Gu, H., and Zhang, X., "Wind Farm Micro-Siting by Gaussian Particle Swarm Optimization with Local Search Strategy",Renewable Energy, Volume 48, No. C, pp. 276-286, 2012
5. Wan, C., Wang, J., Yang, G., and Zhang, X., "Particle Swarm Optimization Based on Gaussian Mutation and its Application to Wind Farm Micro-Siting",49th IEEE Conference on Decision and Control (CDC), pp. 2227-2232, July, 2015
6. Ting, T.O., Yang, X.-S., Cheng, S., and Huang, K., "Hybrid Metaheuristic Algorithms: Past, Present, and Future", Studies in Computational Intelligence, Volume 585, pp. 71-83, 2015
7. Barnett, G.L., Funke, S.W., and Piggott, M.D., "Hybrid Global-Local Optimisation Algorithms for the Layout Design of Tidal Turbine Arrays", arXiv:1410.2476v1 [math.OC], pp. 1-36, 9th October, 201
8. Tesauro, A., Rethore, P.-E., and Larsen, G.C., "State of the Art of Wind Farm Optimization", European Wind Energy Conference & Exhibition, pp. 1-11, 2012
9. Kusiak, A., and Song, Z., "Design of Wind Farm Layout for Maximum Wind Energy Capture",Renewable Energy, Volume 35, No. 3, pp. 685–694, March, 2010.
10. Funke, S.W., and Team, "OpenTidalFarm",2014. [Online. Available: http://opentidalfarm.readthedocs.org/ en/latest/. Accessed: 21stNovember, 2015]
11. Ryanking, "OpenWindFarm",2015. [Online. Available: https://github.com/ryannking/OpenWindFarm. Accessed: 25th November, 2015].
12. Massan, S.-R., Wagan, A.I., and Shaikh, M.M., "Power Optimization of Wind Turbines by the Adjoint Method", Sindh University Research Journal (Science Series), Volume 48, No. 3, pp. 559-562, Jamshoro, Pakistan, 2016.
13. Mosetti, G., Poloni, C., and Diviacco, B., "Optimization of Wind Farms Positioning in Large Wind Farms by Means of a Genetic Algorithm",Wind Engineering and Industrial Aerodynamics, No. 51, pp. 105-116, 1994.
14. Beyer,"Optimization of Wind Farm Configurations with Variable Number of Turbines", Proceedings of European Union Wind Energy Conference, Göteborg, pp. 1073-1076, May, 1996
15. Barthelmie, R., Pryor, S., Frandsen, S., and Larsen, S., "Analytical Modelling of Large Wind Clusters", Proceedings of Special Topic Conference: The Science of Making Torque from Wind, Delft, pp. 292-303, April, 2004
16. Grady, S.A., Hussaini, M.Y., and Abdullah, M.M., "Placement of Wind Turbines using Genetic Algorithms", Renewable Energy, Volume 1, No. 30, pp. 259-270, 2005
17. Wan, C., Wang, J., Yang, G., and Zhang, X., "Optimal Siting of Wind Turbines using Real Coded Genetic Algorithms",National High Technology Research and Development Program in China, 2007.
18. Marmidis, G., Lazarou, S., and Pyrgioti, E., "Optimal Placement of Wind Turbines in a Wind Park using Monte Carlo Simulation", Renewable Energy, No. 33, pp. 1455-1460, 2008
19. Jos´e-Francisco, H.-A., Valenzuela-Rend´on, M., Oliver, P.-O., and Jorge-Rodolfo, F.-A., "Linear Wind Farm Layout Optimization through Computational Intelligence", Instituto Tecnol´ogico y de Estudios Superiores de Monterrey, Campus Monterrey, Eugenio Garza Sada 2501 Sur, Monterrey, N.L., M´exico, CP 64849, 2009
20. Kusiak, A., and Haiyang, Z., "Optimization of Wind Turbine Energy and Power Factor with an Evolutionary Computation Algorithm", Energy, Volume 35, pp. 1324-1332, 2010
21. Palmaa, J.M.L.M., Castro, F.A., Ribeiro, L.F., Rodrigues, A.H., and Pinto, A.P., "Linear and Nonlinear Models Inwind Resource Assessment and Wind Turbine MicroSiting in Complex Terrain",Journal of Wind Engineering and Industrial Aerodynamics, Volume 96, pp. 2308-2326, 2008
22. Wan, C., Wang, J., Yang, G., Li, X., and Zhang, X., "Optimal Micro-Siting of Wind Turbines by Genetic Algorithms Based on Improved Wind and Turbine Models", Proceedings of IEEE 48th Chinese Conference on Decision and Control, pp. 5092-5096, December, 2009
23. Emami, A., and Nougreh, P., "New Approach on Optimization in Placement of Wind Turbines within Wind Farm by Genetic Algorithms", Renewable Energy, No. 35, pp. 169-178, 2010.
24. Rasuo, B.P., and Bengin, A.C., "Optimization of Wind Farm Layout", FME Transactions, Volume 38, No. 3, pp 107-114, 2010.
25. Lazarou, S., Vita, V., and Ekonomou, L., "Application of Powell’s Optimisation Method for the Optimal Number of Wind Turbines in a Wind Farm", Science, Measurement & Technology, Volume IET 5, No. 3, pp. 77-80, 2011
26. Mora, J.S., Gonza´lez, J.C., Santos, J.R., Payan, M.B., and Rodriguez, A.G.G., "Optimization of Wind Farm Turbines Layout using an Evolutive Algorithm", Renewable Energy, Volume 35, No. 8, pp. 1671-1681, 2010
27. González, J.S., Payán, M.B., Santos, J.M.R., and González-Longatt, F., "A Review and Recent Developments in the Optimal Wind-Turbine MicroSiting Problem", Renewable and Sustainable Energy Reviews, No. 30, pp. 133-144, 2014
28. Glover, F., "Future Paths for Integer Programming and Links to Artificial Intelligence", Computers and Operations Research, Volume 13, No. 5, pp. 533-549, 1986.
29. Karampelas, P., Ekonomou, L., Fotis, G.P., and Vita, V., "Evaluation of the Optimal Number of Wind Turbines in a Wind Farm Using the Downhill Simplex Optimization Method", International Journal on Power System Optimization, Volume 3, No. 1, pp. 11-14, 2011.
30. Ituarte-Villarreal, C.M., and Espiritu, J.F., "Optimization of Wind Turbine Placement using a Viral Based Optimization Algorithm", Procedia Computer Science, Volume 6, pp. 469-474, 2011.
31. Chowdhury, S., Zhang, J., Messac, A., and Castillo, L., "Unrestricted WInd Farm Layout Optimization (UWFLO): Investigating Key Factors Influencing the Maximum Power Generation", Renewable Energy, Volume 38, No. 1, pp. 16-30, 2012
32. Song, M.X., Chen, K., He, Z.Y., and Zhang, X., "Wake Flow Model of Wind Turbine using Particle Simulation" ,Renewable Energy, Volume 41, pp. 185-190, 2012
33. Jensen, N.O., "A Note on Wind Generator Interaction", RISO-M-2411, 198
34. Song, M.X., Chen, K., He, Z.Y., and Zhang, X., "Optimization of Wind Farm Micro-Siting for Complex Terrain using Greedy Algorithm", Energy, Volume 67, pp. 454-459, 2014
35. Rehmani, R., Khairuddin, A., Cherati, S.M., and Pesaran, M.H.A., "A Novel Method for Optimal Placing Wind Turbines in a Wind Farm Using Particle Swarm Optimization (PSO)", Proceedings of IEEE Conference on IPEC, pp. 134-139, 2010.
36. Chen, Y., Li, H., Jin, K., and Song, Q., "Wind Farm Layout Optimization using Genetic Algorithm with Different Hub Height Wind Turbines", Energy Conversion and Management, Volume 70, pp. 56-65, June, 2013.
37. Gaumond, M., Réthoré, P.E., Bechmann, A., Ott, S., Larsen, G.C., Pena Diaz, A., and Kurt, K.S., "Benchmarking of Wind Turbine Wake Models in Large Offshore Windfarms", Proceedings of Science of Making Torque from Wind, pp. 10-16, 2012.
38. Rao, A.R.M., and Shyju, P.P., "Development of a Hybrid Meta-Heuristic Algorithm for Combinatorial Optimisation and its Application for Optimal Design of Laminated Composite Cylindrical Skirt", Computers and Structures, Volume 86, No. 7-8, pp. 796-815, 2008
39. Salcedo-Sanz, S., Xu, Y., and Yao, X., "Hybrid MetaHeuristics Algorithms for Task Assignment in Heterogeneous Computing Systems", Computers and Operations Research, Volume 33, No. 3, pp. 820-835, 2006
40. Shahsavari-Pour, N., and Ghasemishabankareh, B., "A Novel Hybrid Meta-Heuristic Algorithm for Solving Multi Objective Flexible Job Shop Scheduling", Journal of Manufacturing Systems, Volume 32, No. 4, pp. 771-780, 2013
41. Lozano, M., and García-Martínez, C., "Hybrid Metaheuristics with Evolutionary Algorithms Specializing in Intensification and Diversification: Overview and Progress Report", Computers and Operations Research, Volume 37, No. 3, pp. 481-497, 2010
42. Leung, S.C.H., Zhang, D., Zhou, C., and Wu, T., "A Hybrid Simulated Annealing Metaheuristic Algorithm for the Two-Dimensional Knapsack Packing Problem", Computers and Operations Research, Volume 39, No. 1, pp. 64-73, 2012.
43. Poorzahedy, H., and Rouhani, O.M., "Hybrid MetaHeuristic Algorithms for Solving Network Design Problem", European Journal of Operational Research, Volume 182, No. 2, pp. 578-596, 2007.
44. Yi, H., Duan, Q., and Liao, T.W., "Three Improved Hybrid Metaheuristic Algorithms for Engineering Design Optimization", Applied Soft Computing Journal, Volume 13, No. 5, pp. 2433-2444, 2013
45. Fattahi, P., Hajipour, V., and Nobari, A., "A Bi-Objective Continuous Review Inventory Control Model: ParetoBased Meta-Heuristic Algorithms", Applied Soft Computing, Volume 32, pp. 211-223, 2015.
46. Massan, S.-R., Wagan, A.I., Shaikh, M.M., and Shah, M.S., "Application of Differential Evolution Algorithm for Wind Turbine Micrositing", Mehran University Research Journal of Engineering & Technology, Volume 36, No. 2, pp. 353-366, Jamshoro, Pakistan, April, 2017
47. Betz, A., "Betz’s Law", [Online. Available: http:// en.wikipedia.org/wiki/Betz’_law] pp. 1, 2016 (Accessed on 1st November, 2016)
48. Wikipedia, "Wind Turbine Aerodynamics - Axial Induction Facto", 2016. [Online. Available: https:// en.wikipedia.org/wiki/Wind-turbine_aerodynamics. Accessed: 20th September, 2016].
49. Wikipedia, "Differential Evolution Algorithm",2014. [Online. Available: http://en.wikipedia.org/wiki/ Differential_evolution. Accessed: 27th July, 2014].
50. Lee, J.B., "Clever Algorithms - Nature Inspired Programming Recipes", Melbourne, 2011
51. Teo, J., "Exploring Dynamic Self-Adaptive Populations in Differential Evolution", Soft Computing, No. 10, pp. 673-686, 2006
52. Yang, X.-S., "Firefly Algorithms for Multimodal Optimization",Stochastic Algorithms: Foundations and Applications, pp. 169-178, 2009.
53. Yang, X.-S., "Firefly Algorithm, Stochastic Test Functions and Design Optimisation", International Journal of Bio-Inspired Computation, pp. 1-12, 2010
54. Wikipedia, "Firefly Algorithm", 2014. [Online. Available: http://en.wikipedia.org/wiki/Firefly_algorithm. Accessed27th July, 2014].
55. Yang, X.-S., "Firefly Algorithm, Levy Flights and Global Optimization", International Journal of Bio-Inspired Computation, 2010.
56. Yang, X.-S., "Introduction to Computational Mathematics", 2nd Edition, World Scientific, 2014
57. Zachariadis, E.E., Tarantilis, C.D., and Kiranoudis, C.T., "A Hybrid Metaheuristic Algorithm for the Vehicle Routing Problem with Simultaneous Delivery and PickUp Service",Expert Systems with Applications, Volume 36, No. 2, pp. 1070-1081, March, 2009