An Experimental Fuzzy Expert System Based Application For The Go/No-Go Decisions To The Geospatial Investigation Studies Of The Regions Of The Very Large Concentrated Solar Power Plants In The European Supergrid Concept

Abstract

One of the crucial activities of today's world electricity research groups is the investigation of the modeling possibility of the international grids on the concepts of the Supergrids and the Globalgrid. The European Supergrid Concept is one of the concepts in this respect. The solar power is one of the important renewable energy resource in the European Supergrid Concept. The concentrated solar power technology is one of the solar power technologies amongst the solar power technologies. The engineering, procuring, constructing and operating of the very large concentrated solar power plants in the European Supergrid Concept shall be one of the ways to escape from the consumption of fossil fuels. This paper performs an experimental one node Mamdani type fuzzy rule base evaluation approach or application for the go/no-go decisions to the geospatial investigation studies of the regions of the very large concentrated solar power plants in the European Supergrid Concept. 

Keywords

• Fuzzy Logic,Concentrated Solar Power,Concentrated Solar Thermal,Concentrating Solar Power,Electricity,Energy,European Supergrid,Fuzzy Expert System,Fuzzy Inference System,Fuzzy Rule Base System,Geo-spatial Investigation,Mamdani,Power,Solar,Solar Power,Sugeno,Supergrid

References

1. [1] European Commission: Impact Assessment On The EU’s Objectives On Climate Change And Renewable Energy. 2008
2. [2] (2014) Friends of the Supergrid website. [Online]. Available: http://www.friendsofthesupergrid.eu/
3. [3] International Energy Agency: World Energy Outlook 2010, OECD/IEA, Paris. 2010
4. [4] International Energy Agency: Technology Roadmap: Concentrating Solar Power, OECD/IEA, Paris. 2010
5. [5] The International Energy Agency (IEA), Technology Roadmap Solar Thermal Electricity, 2014
6. [6] J. Clifton, and B. J. Boruff, “Assessing the potential for concentrated solar power development in rural Australia”, Energy Policy, vol.: 38, pp.5272–5280. 2010
7. [7] A. A. Merrouni, Ab. Mezrhab, and A. Mezrhab, “CSP sites suitability analysis in the Eastern region of Morocco”, Energy Procedia, vol.: 49, pp.2270 – 2279. 2014
8. [8] J. V. Hoesen, and S. Letendre, “Evaluating potential renewable energy resources in Poultney, Vermont: A GIS-based approach to supporting rural community energy planning”, Renewable Energy, vol: 35, pp.2114–2122. 2010

9. [9] Y. Charabi, and A. Gastli, “GIS assessment of large CSP plant in Duqum, Oman”, Renewable and Sustainable Energy Reviews, vol.: 14, pp. 835–841, 2010
10. [10] The Friends of the Supergrid Working Group 2, (2014) Roadmap to the Supergrid Technologies, [Online]. Available http://www.friendsofthesupergrid.eu/wp-content/uploads/2014/06/WG2_Supergrid-Technological-Roadmap_20140622_final.pdf
11. [11] (2014) ACM Digital Library, [Online]. Available: http://dl.acm.org/
12. [12] (2014) ASCE Online Research Library, [Online]. Available: http://ascelibrary.org/
13. [13] (2014) American Society of Mechanical Engineers, [Online]. Available: http://asmedigitalcollection.asme.org/
14. [14] (2014) Cambridge Journals Online, [Online]. Available: http://journals.cambridge.org
15. [15] (2014) Directory of Open Access Journals, [Online]. Available: http://doaj.org
16. [16] (2014) Emerald Insight, [Online]. Available: http://www.emeraldinsight.com/
17. [17] (2014) Google Scholar, [Online]. Available: http://scholar.google.com.tr/
18. [18] (2014) Journal of Industrial Engineering and Management, [Online]. Available: http://www.jiem.org/index.php/jiem
19. [19] (2014) Science Direct, [Online]. Available: http://www.sciencedirect.com
20. [20] (2014) Springer, [Online]. Available: http://www.springer.com/?SGWID=5-102-0-0-0
21. [21] (2014) Taylor & Francis Online/Journals, [Online]. Available: http://www.tandfonline.com/
22. [22] (2014) Wiley-Blackwell/Wiley Online Library, [Online]. Available: http://onlinelibrary.wiley.com/
23. [23] (2014) World Scientific Publishing, [Online]. Available: http://www.worldscientific.com/
24. [24] R. Morales, F. Valencia, D. Sáez, and M. Lacalle, “Supervisory Fuzzy Predictive Control for a Concentrated Solar Power Plant,” in The 19th World Congress, The International Federation of Automatic Control, Cape Town, South Africa. August 24-29, 2014, pp. 1459–1464.
25. [25] R. Chauvin, J. Nou, S. Thil, and S. Grieu, “Intra-Day DNI Forecasting Under Clear Sky Conditions Using ANFIS,” in The 19th World Congress, The International Federation of Automatic Control, Cape Town, South Africa. August 24-29, 2014, pp. 10361–10366.
26. [26] (2014) Wikimedia Foundation- Experiment, [Online]. Available: http://en.wikipedia.org/wiki/Experiment
27. [27] (2014) National Center for Technology Innovation, [Online]. Available: http://www.nationaltechcenter.org/index.php/products/at-research-matters/experimental-study-design/
28. [28] M. J. Wierman, An Introduction to the Mathematics of Uncertainty including Set Theory, Logic, Probability, Fuzzy Sets, Rough Sets, and Evidence Theory. Center for the Mathematics of Uncertainty. Creighton University College of Arts and Sciences. 2010
29. [29] G. J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic Theory and Applications. Prentice Hall. 1995
30. [30] N. K. Kasabov, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering. MIT Press. 1998
31. [31] J. F. Sowa, “What Is the Source of Fuzziness? Studies,” in Fuzziness and Soft Computing Volume 299, pp 645-652. 2013
32. [32] (2014) National Geographic Society, Brain Games, [Online]. Available: http://video.nationalgeographic.com/video/brain-games
33. [33] Harpaz, Y. (1994) The Mechanisms of Human Cognition, [Online]. Available: http://human-brain.org/cognition.html,
34. [34] L.A. Zadeh, (2014) e-mail subject: Correction: Translation, summarization, understanding and world knowledge/ Chomsky‏, date: 03/07/2014.
35. [35] (2014) Oxford University Press, Oxford Dictionaries, [Online]. Available: http://www.oxforddictionaries.com /definition /english/fuzzy
36. [36] (2014) Merriam-Webster Incorporated, [Online]. Available: http://www.merriam-webster.com/dictionary/fuzzy
37. [37] L.A. Zadeh, “Fuzzy sets,” Information and Control vol. 8, pp.338–353. 1965
38. [38] (2014) Wikimedia Foundation- Lotfi A. Zadeh, [Online]. Available: http://en.wikipedia.org/wiki/Lotfi_A._Zadeh
39. [39] E.H. Mamdani, “Application of fuzzy algorithms for control of simple dynamic plant. Proceedings of the Institution of Electrical Engineers,” vol. 121, iss. 12, pp.1585–1588. 1974
40. [40] T. Takagi, M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” IEE Transactions on Systems, Man and Cybernetics vol. 15, no: 1, 116–132, 1985.
41. [41] C.C. Lee, “Fuzzy Logic in Control Systems: Fuzzy Logic Controller-Part I,” IEE Transactions on Systems, Man and Cybernetics vol. 20, no: 2, pp.404–418, 1990.
42. [42] (2014) The MathWorks-Comparison of Sugeno and Mamdani Systems, [Online]. Available: http://www.mathworks.com/help/fuzzy/comparison-of-sugeno-and-mamdani-systems.html
43. [43] A.A. Shleeg, and I.M. Ellabib, “Comparison of Mamdani and Sugeno Fuzzy Interference Systems for the Breast Cancer Risk,” World Academy of Science, Engineering and Technology International Journal of Computer, Information, Systems and Control Engineering, vol:7 no:10, 695–699, 2013.
44. [44] A. Kaur, and A. Kaur, “Comparison of Mamdani-Type and Sugeno-Type Fuzzy Inference Systems for Air Conditioning System,” International Journal of Soft Computing and Engineering (IJSCE), vol: 2, issue: 2, 323–325, 2012.
45. [45] M.A. Salman, and N.I. Seno, “A Comparison of Mamdani and Sugeno Inference Systems for a Satellite Image Classification,” Anbar Journal for Engineering Sciences, vol:0, issue:0, 296–306, 2012.
46. [46] Saracoglu, B. O. The Location Selection Factors Of Very Large Concentrated Solar Power Plant Investments in the Supergrid and the Globalgrid Concepts, In review. 2014
47. [47] (2014) National Renewable Energy Laboratory (NREL), [Online]. Available: http://rredc.nrel.gov/solar/glossary/gloss_d.html
48. [48] S.M. Lewis, S. Gross, A. Visel, M. Kelly, and W. Morrow, “Fuzzy GIS-based multi-criteria evaluation for US Agave production as a bioenergy feedstock,” Global Change Biology Bioenergy, pp.1–16, 2014.
49. [49] H. Chaudhary, and S. Jain, “Identifying solar suitability of a region using Fuzzy logic,” Proc. of the Intl. Conf. on Advances in Computer Science and Electronics Engineering CSEE, pp.65–69, 2013.
50. [50] L.C. Scott, and J.W. Boland, “Predicting the Diffuse Fraction of Global Solar Radiation using Regression and Fuzzy Logic,” in Proceedings of the 37th Annual Conference of the Australia & NZ Energy Society, Sola 99, 1999, Geelong, Australia, 01-DEC-99
51. [51] (2014) GeoModel Solar, [Online]. Available: http://solargis.info/doc/free-solar-radiation-maps-DNI.
52. [52] S. Pradibtha, I.N. Piarsa, and P.W.B. Ana, “Residential Site Selection By Combining GIS And Fuzzy Database Query On Android Device,” Journal of Theoretical and Applied Information Technology, vol. 61, no.3, pp. 654–660, 2014.
53. [53] K. Wang, Z. Li, and J. Zhou, “Two Decision-making Approaches to Fire Station Location,” Fuzzy Environment, Journal of Information & Computational Science, vol:11, no:13 pp.4779–4793, 2014.
54. [54] T.Y. Chou, C.L. Hsu, and M.C. Chen, “A fuzzy multi-criteria decision model for international tourist hotels location selection,” International Journal of Hospitality Management, vol:27, pp.293–301, 2008.
55. [55] S. Hwang, and J.C. Thill, “Modeling Localities with Fuzzy Sets and GIS,” Fuzzy Modeling with Spatial Information for Geographic Problems, pp.71–104, 2005.
56. [56] P. Collier, and N. Sambanis, Understanding Civil War Evidence and Analysis Volume 1: Africa, The International Bank for Reconstruction and Development / The World Bank, Washington DC. 2005.
57. [57] S. Grimm, and G. Schneider, “Predicting social tipping points current research and the way forward,” German Development Institute, Discussion Paper, 8, 2011.
58. [58] J.J. Xenakis, “International business forecasting using system dynamics with generational flows,” Generational Dynamics white paper. 2009.
59. [59] M.O. Jackson, and M. Morelli, The Reasons for Wars – an Updated Survey. 2009.
60. [60] K. Hirose, K. Imai, and J. Lyall, “Can Civilian Attitudes Predict Civil War Violence?” Social Science Research Network, [Online]. Available: at SSRN: http://ssrn.com/abstract=2446168 or http://dx.doi.org/10.2139/ssrn.2446168 .(2014)
61. [61] D.C. Garlow, Civil War Prediction and Insurance against Political Violence. [Online]. Available: www.vanderbilt.edu/econ/conference/gped-conference-06/papers/garlow.pdf
62. [62] M. Ghomshei, J. Meech, and R. Naderi, “War, Peace and Fuzzy Logic,” Cybernetics and Systems, volume 39, issue 2, pp.113–135, 2008.
63. [63] J. Talasova, and P. Holecek, “Multiple-Criteria Fuzzy Evaluation: The FuzzME Software Package,” in IFSA/EUSFLAT Conference, 2009, pp. 681–686.
64. [64] (2014) The website of FuzzME, [Online]. Available: http://www.fuzzme.net, http://fuzzme.wz.cz/
65. [65] R. Likert, “A Technique For The Measurement Of Attitudes,” Archives Of Psychology, no: 140, New York, USA. 1932.
66. [66] L.A. Zadeh, “A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges,” Journal of Cybernetics, vol: 2, issue: 3, pp.4–34, 1972.
67. [67] G.A. Miller, “The magical number seven, plus or minus two: some limits on our capacity for processing information,” The Psychological Review, No.63, pp.81–97, 1956.
68. [68] R.M. Shiffrin, and R.M. Nosofsky, “Seven plus or minus two: a commentary on capacity limitations,” Psychological Review, vol:101, issue:2, pp.357–361, 1994.
69. [69] (2014) The Department of Homeland Security, Citizen Guidance on the Homeland Security Advisory System, [Online]. Available: www.dhs.gov/xlibrary/assets/citizen-guidance-hsas2.pdf