A Study on Wind and Solar Energy Potentials in Malaysia
Abstract
This paper discusses the wind and solar energy potentials in Malaysia. It first presents the Weibull density functions and compares the wind speed over several cities. Then, it shows the power density at the wind measurement device’s height and compares it with the power density at the hub height of a certain turbine, followed by showing the probability of the turbines operating above 2.5m/s and their annual operating hours. The second part presents temperature and radiation over the same cities and compares the output energy of a specific PV module in each of the cities; to provide a fair comparison. All the data are from the Malaysian Meteorology Department, and they were taken from 2011-2012 on a daily basis. The significance of this research is that it lays the road for optimization studies and gives a glimpse on the energy potential of the wind and solar energies in Malaysia.
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Global Wind Energy Council. Annual report, 2012. [online] available at: http://www.gwec.net/wp-content/uploads/2012/06/Annual_report_2012_LowRes.pdf
bp. Statistical review 2013.[online] available at http://www.bp.com/en/global/corporate/about-bp/energy-economics/statistical-review-of-world-energy-2013/statistical-review-downloads.html
Sumiani Yuosoff, Roozbeh Kardooni, “Barriers and challenges for developing RE policy in Malaysiaâ€, International Conference on Future Environment and Energy IPCBEE, vol. 28,2012.
IK.H. Solangi, T.N.W. Lwin, N.A. Rahim, IM.S. Hossain, IR. Saidur, IH. Fayaz, “Development of Solar Energy and Present Policies in Malaysiaâ€, IEEE First Conference on Clean Energy and Technology CEAT, 2011.
Malaysian Meteorology Department. [online] Available at: http://www.met.gov.my/index.php?option=com_content&task=view&id=75&Itemid=1089
H.C. Ong, T.M.I. Mahlia, H.H. Masjuki, “A review on energy scenario and sustainable energy in Malaysiaâ€, Renewable and Sustainable Energy Reviews, vol. 15, pp. 639–647, 2011.
K. Ulgen, and A.Hepbasli, “Determination of Weibull parameters for wind energy analysis of Ä°zmirâ€, Turkey. Int. J. Energy Res, vol. 26, pp. 495–506, 2012.
Liu Yuehua, Jiang Yingni, Gong Qingge, “Analysis of Wind Energy Potential Using the Weibull Model at Zhuriheâ€, IEEE 978-1-61284-459-6/11/, 2011.
G. Johnson, Wind energy systems. Electronic edition, 2006.
Mohamed Abbes, Jamel Belhadj, “Investigation of Wind Characteristics and Wind Power Potential in EL-Kef Region, Tunisiaâ€, IEEE 8th International Multi-Conference on Systems, Signals & Devices, 2011.
Tai-Her Yeh and Li Wang, “A Study on Generator Capacity for Wind Turbines under Various Tower Heights and Rated Wind Speeds Using Weibull Distributionâ€, IEEE Transactions on Energy Conversion, vol. 23, no. 2, 2008.
B. Dursun, B. Alboyaci, “An Evalution of Wind Energy Characteristics for four Different Locations in Balikesirâ€, Energy Sources, Part A, 33:1086-1103, 2011.
Lin Lu, Hongxing Yang, John Burnett, “Investigation on wind power potential on Hong Kong islands-an analysis of wind power and wind turbines characteristicsâ€, Renewable Energy 27, pp.1-12, 2002.
Ali Keyhani, Design of Smart Power Grid renewable Energy System, 1st edition, John Wiley &Sons, Inc. 2011.
M. Fuentes, G. Nofuentes, J. Aguilera, D.L. Talavera, M. Castro, “Application and validation of algebraic methods to predict the Behavior of crystalline silicon PV modules in Mediterranean climatesâ€, Solar Energy, vol 81, issue 11, 2007.
National Renewable Energy Laboratory (NREL). [online]. Available at http://www.nrel.gov/rredc/pvwatts/changing_parameters.html
Walid Omran, Performance analysis of grid-connected photovoltaic systems, Ph.D. dissertation. University of Waterloo, 2010.
Ann Marie Borbely, Jan F. Kreider, Distributed Generation : The Power Paradigm for the New Millennium, New York Washington, D.C.: CRC Press Boca Raton London, 2001.
DOI (PDF): https://doi.org/10.20508/ijrer.v4i4.1761.g6445
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