ANN AND GIS-ASSISTED METHODOLOGY FOR WIND RESOURCE ASSESSMENT (WRA) IN SARAWAK
DOI:
https://doi.org/10.11113/jt.v77.6311Keywords:
GIS, wind energy, power density, kriging interpolation, SarawakAbstract
Wind energy is a reliable, clean source and has emerged as one of the dependable, and the best performing developing renewable energy around the world. It has insignificant environmental impacts, compared to other energy sources. In Sarawak, Malaysia, wind resource varies depending on the location. An inadequate number of wind stations are the major obstacles that slow down the growing of green energy in the region. Site selection is a crucial issue for potential investors and policy makers. This paper examines the spatial distribution and the amount of potential wind power and energy densities for wind energy production and suitable locations in Sarawak. A geographical Information System (GIS) assisted methodology, which includes wind speed, power and energy densities using the existing wind station and based on the newly developed prediction model called topographical neural network (TNN) were used. Kriging interpolation was employed for a simple interpolation of data between locations. The results show that the northeast, northwest and coastal regions have better prospects of wind energy. The studied GIS methodology can be applied for identification of the most suitable locations for wind energy harvesting. The developed maps can further be used in micro-siting and economic evaluation analysis.
References
Lawan, S., W. Abidin, W. Chai, A. Baharun, and T. Masri. Reviewing Wind Speed and Energy Distribution in Malaysia.
Lawan, S., W. Abidin, W. Chai, A. Baharun, and T. Masri. 2013. The Status Of Wind Resource Assessment (Wra) Techniques, Wind Energy Potential And Utilisation In Malaysia And Other Countries. Journal of Engineering & Applied Sciences. 8.
RamÃrez, P. and J. A. Carta. 2006. The Use of Wind Probability Distributions Derived from the Maximum Entropy Principle in the Analysis of Wind Energy. A Case Study. Energy Conversion and Management. 47: 2564-2577.
Fadare, D. 2010. The Application of Artificial Neural Networks to Mapping of Wind Speed Profile for Energy Application in Nigeria. Applied Energy. 87: 934-942.
Merzouk, N. K. 2000. Wind Energy Potential of Algeria. Renewable Energy. 21: 553-562.
Kose, R., M. A. Ozgur, O. Erbas, and A. Tugcu. 2004. The Analysis of Wind Data and Wind Energy Potential in Kutahya, Turkey. Renewable and Sustainable Energy Reviews. 8: 277-288.
Lackner, M. A., A. L. Rogers, and J. F. Manwell. 2008. The Round Robin Site Assessment Method: A New Approach to Wind Energy Site Assessment. Renewable Energy. 33: 2019-2026.
Malik, A. S. and C. Kuba. 2013. Power Generation Expansion Planning Including Large Scale Wind Integration: A Case Study of Oman. Journal of Wind Energy.
Mirza, U. K., N. Ahmad, T. Majeed, and K. Harijan. 2007. Wind Energy Development in Pakistan. Renewable and Sustainable Energy Reviews. 11: 2179-2190.
Avdakovic, S., A. Lukac, A. Nuhanovic, and M. Music. 2011. Wind Speed Data Analysis using Wavelet Transform.
Anderson, R., S. Ali, L. Bradtmiller, S. Nielsen, M. Fleisher, B. Anderson, and L. Burckle. 2009. Wind-driven Upwelling in the Southern Ocean and the Deglacial Rise in Atmospheric CO2. Science. 323: 1443-1448.
Keyhani, A., M. Ghasemi-Varnamkhasti, M. Khanali, and R. Abbaszadeh. 2010. An Assessment of Wind Energy Potential as a Power Generation Source in the Capital of Iran, Tehran. Energy. 35: 188-201.
Ahmed, S. and H. Mahammed. 2012. A Statistical Analysis of Wind Power Density based on the Weibull and Ralyeigh Models of “Penjwen Region†Sulaimani/Iraq. Jordan J. Mech. Ind. Eng. 6: 135-140.
Rehman, S. and A. Ahmad. 2004. Assessment of Wind Energy Potential for Coastal Locations of the Kingdom of Saudi Arabia. Energy. 29: 1105-1115.
Eltamaly, A. M. 2014. Pairing Between Sites and Wind Turbines for Saudi Arabia Sites. Arabian Journal for Science and Engineering. 39: 6225-6233.
Chaichana, T. and S. Chaitep. 2010. Wind Power Potential and Characteristic Analysis of Chiang Mai, Thailand. Journal of Mechanical Science And Technology. 24: 1475-1479.
Dike, V. N., ChinekeC.T. , NwoforO.K. , and O. K. 2011. Wind Energy Potential in Some Coastal Cities of Niger-Delta Region of Nigeria. The Pacific Journal odf Science and Technology. 12: 598-604.
Omer, A. M. 2008. On the Wind Energy Resources of Sudan. Renewable and Sustainable Energy Reviews. 12: 2117-2139.
Carta, J. and P. Ramirez. 2007. Analysis of Two-component Mixture Weibull Statistics for Estimation of Wind Speed Distributions. Renewable Energy. 32: 518-531.
Philippopoulos, K. and D. Deligiorgi. 2009. Statistical Simulation of Wind Speed in Athens, Greece Based on Weibull and ARMA Models. International Journal of Energy and Environment. 3: 151-158.
Hadley, S. W. and W. Short. 2001. Electricity Sector Analysis in the Clean Energy Futures Study. Energy Policy. 29: 1285-1298.
Ahmad, S., M. Z. A. A. Kadir, and S. Shafie. 2011. Current Perspective of the Renewable Energy Development in Malaysia. Renewable and Sustainable Energy Reviews. 15: 897-904.
Ahmad, S., B. MA, and M. S. SA. 1995. Analysis of Wind Speed Variations and Estimation of Weibull Parameters for Wind Power Generation in Malaysia.
Albani, A. and M. Ibrahim. 2014. An Assessment of Wind Energy Potential for Selected Sites in Malaysia Using Feed-in Tariff Criteria. Wind Engineering. 38: 249-260.
Albani, A., M. Ibrahim, and K. Yong. 2009 Investigation on Wind Energy Potential at Sabah State of Malaysia. In 10th UMT International Annual Symposium on Empowering Science, Technology and Innovation Towards a Better Tomorrow. 11-13.
Albani, A., M. Ibrahim, and K. Yong. 2014. The Feasibility Study of Offshore Wind Energy Potential in Kijal, Malaysia: The New Alternative Energy Source Exploration In Malaysia. Energy, Exploration & Exploitation. 32: 329-344.
Anyi, M., B. Kirke, and S. Ali. 2010. Remote Community Electrification in Sarawak, Malaysia. Renewable Energy. 35: 1609-1613.
Darus, Z. M., A. Chawdar, O. A. Karim, and K. A. Maulud. 2009 The Appraisal of Energy Policies and Potential of Renewable Energy as Alternative Source of Energy in Malaysia. In Proceedings of the 3rd WSEAS Int. Conf. on Energy Planning, Energy Saving, Environmental Education, 2009. 32-37.
Islam, M., N. Rahim, K. Solangi, and R. Saidur. 2012. Assessing Wind Energy Potentiality for Selected Sites in Malaysia. Energy Education Science and Technology Part A-Energy Science and Research. 29: 611-626.
Ab. Wahab, A. 2004. Title. unpublished.
Jakhrani, A., A. Othman, A. Rigit, and S. Samo. 2013. Assessment of Solar and Wind Energy Resources at Five Typical Locations in Sarawak. Journal of Energy and Environment. 4.
Lawan, S., W. Abidin, W. Chai, A. Baharun, and T. Masri. Different Models of Wind Speed Prediction; A Comprehensive Review.
Abdeladim, K., R. Romeo, and S. Magri. 1996. Wind Mapping of a Region in the North-East of Algeria. Renewable Energy. 9: 789-793.
Manwell, J., J. McGowan, and A. Rogers. 2002. Wind Energy Explained: Theory, Design and Application. John Wiley&Sons Ltd, UK. 577.
Akinci, T. 2011. Short Term Wind Speed Forecasting with ANN in Batman, Turkey. Electronics & Electrical Engineering. 1: 41-45.
Carolin Mabel, M. and E. Fernandez. 2008. Analysis of Wind Power Generation and Prediction Using ANN: A Case Study. Renewable Energy. 33: 986-992.
Chen, L. and X. Lai. 2011 Comparison between ARIMA and ANN Models Used in Short-Term Wind Speed Forecasting. In Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific. 1-4.
Chellali, F., A. Khellaf, A. Belouchrani, and A. Recioui. 2011. A Contribution In The Actualization Of Wind Map Of Algeria. Renewable and Sustainable Energy Reviews. 15: 993-1002.
Khan, M., M. Iqbal, and S. Mahboob. 2004. A wind map of Bangladesh. Renewable Energy. 29: 643-660.
Ahmad, A. and T. Anderson. 2014 Global Solar Radiation Prediction Using Artificial Neural Network Models for New Zealand.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
