Research of the Risks that are Originated from Topographic Terrestrial Observations in Wind Energy Power Plant Projects

Year 2020, , 741 - 752, 25.09.2020

Eray Can , Hikmet Erbıyık

https://doi.org/10.35414/akufemubid.664701

Cited By: 2

Abstract

In our days, in order to increase the social prosperity of the nations and gaining competitive advantage against the other nations, the share of the energy is prominent. Nowadays the increase of populations in the nations and as a result of this situation; the increase of urbanization, industrialization and defence needs, are increasing the energy demand. Again, the human is being forwarded to the alternative energy sources, due to increase of fossil fuel damages into environment, depletion of fossil fuels in a speedy manner and increase of the cost of the fossil fuels, etc. Especially, in the production of sustainable electrical energy, that has an important share among the other energy types; preferring wind energy instead of fossil fuels is consisting of the leading alternative energy sources. In design, implementation and operation of the electrical power plants projects that utilize wind energy, the conformity of the concerned field with the project becoming an important factor. In order to realize this conformity, the engineering measurements that are made in the relevant field are also becoming important. In this study, the failure factors that occurred during the engineering measurements for the establishment of these power plants were examined in the FMEA systematic called Failure Mode Effects Analysis. However, the order of importance of these identified risks is indicated in the Pareto analysis. Beside the preventions that can be taken against these risks are examined by taking into consideration the expert opinions.

Keywords

Wind energy power plants, Engineering measurements, Failure mode effect analysis (FMEA), Pareto analysis, Risk detection

Rüzgâr Enerji Santrali Projelerinde Topografik Yersel Ölçme ve Gözlemlerden Kaynaklanan Risklerinin İncelenmesi

Abstract

Günümüzde ülkelerin toplumsal refahlarının artması ve diğer ülkelerle ileri düzeyde rekabet edebilmelerinde, enerjinin payı oldukça büyüktür. Özellikle son yıllarda, toplumlardaki nüfus artışları ve bu nüfus artışları sonucu; kentleşmenin, sanayileşmenin ve savunmanın öneminin artması, enerji ihtiyacını her geçen gün daha da artırmaktadır. Yine insanoğlu çağımızda; fosil yakıtların çevreye vermiş oldukları zararlarının bulunması, bu yakıt türünün hızla tükenmeye başlaması ve bu yakıt türlerinin maliyetlerinin yüksek olması vb. sebeplerle alternatif enerji kaynaklarına yönelmektedir. Özellikle enerji türlerinin arasında büyük bir paya sahip olan sürdürülebilir elektrik enerjisi üretiminde, fosil yakıtlar yerine, rüzgâr enerjisinden faydalanmak, alternatif enerji kaynaklarının başında gelmektedir. Rüzgâr enerjisi kullanarak elektrik üreten santral projelerinin tasarımında uygulanmasında ve işletilmesinde, projenin tasarlandığı arazinin, projeyle uyumu da önemli bir unsur olmaktadır. Bu uyumun gerçekleşebilmesi için de arazide yapılan mühendislik ölçmeleri son derece önemli olmaktadır. Çalışmada, bu enerji santrallerin tesis edilebilmesi için yapılan mühendislik ölçmeleri sırasında oluşan risk ve hata faktörleri, Hata türü etkileri analizi adı verilen (HTEA) sistematiği içinde araştırılmıştır. Ayrıca belirlenen bu risklerin önem sırası da, Pareto analizi sistematiğinde belirtilmiştir. Yine, karşılaşılabilecek olan bu risklere karşı alınabilecek önlemler, uzman görüşleri dikkate alınarak incelenmiştir.

Keywords

Rüzgar enerji santralleri, Mühendislik ölçmeleri, Hata türü etkileri analizi (HTEA), Pareto Analizi, Risk Belirleme

References

• Ajayi, O.O.,2009. Assessment of utilization of wind energy resources in Nigeria. Energy Policy, (37)(2009): 750–753, https://doi.org/10.1016/j.enpol.2008.10.020
• Akın, B., 1998. ISO 9000 Uygulamasında ve İşletmelerde Hata Türü ve Etkileri Analizi Bilim Teknik Yayınevi, 182s, İstanbul
• Amoo, O.M., 2012. Evaluation of the wind energy potential of two south west sites in Nigeria Frontiers in Energy 6(3): 237-246, https://doi.org/10.1007/s11708-012-0201-2
• Argin, M., Yerci, V., Erdogan, N., Kucuksari, S., Cali, U., 2019. Exploring the offshore wind energy potential of Turkey based on multicriteria site selection, Energy Strategy Reviews 23 (2019): 33–46, https://doi.org/10.1016/j.esr.2018.12.005
• Beccali, M., Cirrincione, G., Marvuglia, A., Serporta, C., 2010. Estimation of wind velocity over a complex terrain using the Generalized Mapping Regressor. Applied Energy, (87)(2010): 884–893, https://doi.org/10.1016/j.apenergy.2009.05.026
• Bosch J, Staffell I, Hawkes, AD (2018) Temporally explicit and spatially resolved global offshore wind energy potentials, Energy, 163 (2018): 766-781, https://doi.org/10.1016/j.energy.2018.08.153
• Brouwer, S.R., Al-Jibouri, S.H.S., Cárdenas, I.C., Halman, J.I.M. (2018). Towards analysing risks to public safety from wind turbines, Reliability Engineering and System Safety 180 (2018): 77–87, https://doi.org/10.1016/j.ress.2018.07.010
• Cellura, M., Cirrincione, G., Marvuglia, A., Miraoui, A., 2008. Wind speed spatial estimation for energy planning in Sicily: A neural kriging application. Renewable Energy, (33)(2008): 1251–1266, https://doi.org/10.1016/j.renene.2007.08.013
• Chin, K.S., Wang, Y.M., Poon Gary Ka, K., Yang, J.B., 2009. Failure mode and effects analysis using a group-based evidential reasoning approach, Computers & Operations Research, 36(2009):1768–1779, https://doi.org/10.1016/j.cor.2008.05.002
• Ervural, B.C., Zaim, S., Demirel, O.F., Aydin, Z., Delen, D., 2018. An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning, Renewable and Sustainable Energy Reviews, 82 (2018): 1538–1550, https://doi.org/10.1016/j.rser.2017.06.095
• Finardi, S., Tinarelli, G., Faggian, P., Brusasca, G., 1998. Evaluation of different wind field modeling techniques for wind energy applications over complex topography, Journal of Wind Engineering and Industrial Aerodynamics 74-76 (1998): 283-294, https://doi.org/10.1016/S0167-6105(98)00025-7
• Ferragut, L., Montenegro, R., Montero, G., Rodrı´guez, E., Asensio, M.I., Escobar, J.M., 2010. Comparison between 2.5-D and 3-D realistic models for wind field adjustment, Journal of Wind Engineering and Industrial Aerodynamics, 98 (2010): 548–558, https://doi.org/10.1016/j.jweia.2010.04.004
• Fang, J., Peringer, A., Stupariu, M.S., Patru-Stupariu, I., Buttler, A., Golay, F., Porté-Agel, F., 2018. Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain, Science of the Total Environment 639 (2018): 374–384, https://doi.org/10.1016/j.scitotenv.2018.05.083
• Gualtieri, G., 2019. A comprehensive review on wind resource extrapolation models applied in wind energy, Renewable and Sustainable Energy Reviews 102(2019): 215–233, https://doi.org/10.1016/j.rser.2018.12.015
• Han, X., Liu, D., Xu, C., Shen, W.Z., 2018. Atmospheric stability and topography effects on wind turbine performance and wake properties in complex terrain, Renewable Energy 126 (2018): 640-651, https://doi.org/10.1016/j.renene.2018.03.048
• Kang, J., Sun, L., Sun, H., Wu, C., 2017. Risk assessment of floating offshore wind turbine based on correlation-FMEA. Ocean Engineering, 129 (2017): 382–388, https://doi.org/10.1016/j.oceaneng.2016.11.048
• Kang, J., Sun, L., Guedes Soares, C., 2019. Fault Tree Analysis of floating offshore wind turbines, Renewable Energy, 133(2019): 1455-1467, https://doi.org/10.1016/j.renene.2018.08.097
• Kim, Y.H., Lim, H.C., 2017. Effect of island topography and surface roughness on the estimation of annual energy production of offshore wind farms, Renewable Energy, 103 (2017): 106-114, https://doi.org/10.1016/j.renene.2016.11.020
• Kucukali, S., 2016. Risk scorecard concept in wind energy projects: An integrated approach, Renewable and Sustainable Energy Reviews, 56(2016): 975–987, https://doi.org/10.1016/j.rser.2015.12.017
• Leimeister, M., Kolios, A., 2018. A review of reliability-based methods for risk analysis and their application in the offshore wind industry, Renewable and Sustainable Energy Reviews 91 (2018): 1065–1076, https://doi.org/10.1016/j.rser.2018.04.004
• Li, J., Yu, X(B)., 2017. LiDAR technology for wind energy potential assessment: Demonstration and validation at a site around Lake Erie, Energy Conversion and Management 144 (2017): 252–261, https://doi.org/10.1016/j.enconman.2017.04.061
• Liu, H.C., Liu, L., Liu, N., 2013. Risk Evaluation Approaches in Failure Mode and Effects Analysis: A Literature Review, Expert Systems with Applications, 40(2013):828-838, https://doi.org/10.1016/j.eswa.2012.08.010
• Liua, F., Sun, F., Liu, W., Wang, T., Wang, H., Wang, X., Lim, W.H., 2019. On wind speed pattern and energy potential in China, Applied Energy 236 (2019): 867–876, https://doi.org/10.1016/j.apenergy.2018.12.056
• Lun, Y.F., Mochida, A., Yoshino, H., Murakami, S., 2007. Applicability of linear type revised k– e models to flow over topographic features, Journal of Wind Engineering and Industrial Aerodynamics, 95 (2007): 371–384, https://doi.org/10.1016/j.jweia.2006.09.004
• Marugána, A.P., Márquez, F.P.G., Perez, J.M.P., Ruiz-Hernández, D., 2018. A survey of artificial neural network in wind energy systems. Applied Energy, 228(2018): 1822–1836, https://doi.org/10.1016/j.apenergy.2018.07.084
• Miryousefi Aval S.M., Ahadi, A., Hayati, H., 2016. A novel method for reliability and risk evaluation of wind energy conversion systems considering wind speed correlation Frontiers in Energy 10(1): 46-56, https://doi.org/10.1007/s11708-015-0384-4
• Nedjari, H.D., Guerri, O., Saighi, M., 2017. CFD wind turbines wake assessment in complex topography, Energy Conversion and Management 138 (2017): 224–236, https://doi.org/10.1016/j.enconman.2017.01.070
• Özcan, S., 2001. İstatiksel Proses Kontrol Tekniklerinden Pareto Analizi ve Çimento Sanayiinde Bir Uygulama Cumhuriyet Universitesi, İktisadi ve İdari Bilimler Dergisi, 2(2):151-174,
• Ramachandra, T.V., Shruthi, B.V., 2005. Wind Energy Potential Mapping in Karnataka, India, using GIS. Energy Conersion and Management, (46)(2005): 1561–1578, https://doi.org/10.1016/j.enconman.2004.07.009
• Rolik, Y., 2017. Risk Management in Implementing Wind Energy Project Procedia Engineering, 178(2017):278 – 288, https://doi.org/10.1016/j.proeng.2017.01.115
• Shafiee, M., Dinmohammadi, F., 2014. An FMEA-Based Risk Assessment Approach for Wind Turbine Systems: A Comparative Study of Onshore and Offshore, Energies, 7(2), 619-642, https://doi.org/10.3390/en7020619
• Shu, Z.R., Li, Q.S., He, Y.C., Chan, P.W., 2016. Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications, Applied Energy 169 (2016): 150–163, https://doi.org/10.1016/j.apenergy.2016.01.135
• Su, X., Deng, Y., Mahadevan, S., Bao, Q., 2012. An Improved Method For Risk Evaluation in Failure Modes and Effects Analysis of Aircraft Engine Rotor Blades, Engineering Failure Analysis, 26(2012): 164-174, https://doi.org/10.1016/j.engfailanal.2012.07.009
• Şen, Z., 1999. Terrain Topography Classification for Wind Energy Generation. Renewable Energy, (16)(1999): 904–907, https://doi.org/10.1016/S0960-1481(98)00304-8
• Tarawneh, Q.Y., Şahin, A.D., 2003. Regional wind energy assessment technique with applications. Energy Conversion and Management, (44)(2003):1563–1574, https://doi.org/10.1016/S0196-8904(02)00164-4
• Tazi, N., Châtelet, E., Bouzidi, Y., 2017. Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis, Energies, 2017, 10(3): 276, https://doi.org/10.3390/en10030276
• Wang, Y.M., Chin, K.S., Poon Gary Ka, K., Yang, J.B., 2009. Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Weighted Geometric Mean, Expert Systems with Applications,36(2009): 1195-1207, https://doi.org/10.1016/j.eswa.2007.11.028
• Xiao, N., Huang, H.Z., Li, Y., He, L., Jin, T., 2011. Multiple Failure Modes Analysis And Weighted Risk Priority Number Evaluation in FMEA, Engineering Failure Analysis, 18(2011):1162-1170, https://doi.org/10.1016/j.engfailanal.2011.02.004
• Xinyao, J., Yongjun, H., Fuchao, L., 2017. Research on the evaluation of wind power projects of investment risk, Procedia Computer Science, 111(2017): 388–398, https://doi.org/10.1016/j.procs.2017.06.039
• Yssaad, B., Abene, A., 2015. Rational Reliability Centered Maintenance Optimization for power distribution systems, Electrical Power and Energy Systems, 73(2015):350–360, https://doi.org/10.1016/j.ijepes.2015.05.015