Electricity in the Republic of Maldives: an Analysis on the Demand, Supply and Prediction of the Future Growth in Male’


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Abstract


The islands of the republic of Maldives, barely 1.5 m above sea level, with 80% of it less than 1m above mean sea level represent only a tiny fraction of the global green house emission and yet, are the most vulnerable to the effects of climate change. In Maldives, electricity is produced only using diesel generators, a method that’s the most expensive and environmentally harmful. The State Electric Company (STELCO) is the main organization fully owned by the government that produces the required electricity in the Maldives and yet caters for about 60% of the population while the remaining 40% is met by the production of Island Development Communities (IDCs) and Non Government Organizations (NGOs). The STELCO power plant in Male’ is the largest power plant in the country and operates with an installed capacity of 50MW, as of December 2010. It is also known as the most reliable facility in the country, and yet has repeatedly failed to meet the demand in Male’ reflecting the operational inefficiency of the facility. This paper critically analyzes the supply and demand of electricity in Male’ based on the data obtained from STELCO head office attempting to identify the possible reasons behind its operational failures in the past. The load demand for the next 15 years was forecasted using multiple linear regression algorithm and it revealed that the growth in demand would reach as high as 140 MW peak within the next fifteen years while 71% of the total electricity produced by STELCO nationwide, is produced and consumed in Male’ alone. The interpretability of the model was tested by comparing the actual demand recorded by STELCO for ten years, to the estimted demand for the same period using the model and the results revealed that the model had good interpretabillity.
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Keywords


Electricity Demand and Supply; Load Forecasting; Multiple Linear Regression Algorithm

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References


National Adaptation Program of Action, Ministry of Environment, Energy and Water, Republic Of Maldives, (2006), retrieved on August12, 2011 from: www.preventionweb.net/files/8466_NAPAmaldives.pdf.

The World Fact Book, CIA, Retrieved on August 12, 2011 from: https://www.cia.gov/library/publications/the-world-factbook/geos/mv.html.

C. Nayar, Wind/PV/diesel micro grid system implemented in remote islands in the Republic of Maldives. In: proceeding IEEE International Conference on Sustainable Energy Technologies, Singapore 2008, pp. 1076 – 1080.

Information obtained from STELCO Head Office in Male’, by ‘Personal communication’.

ADB “Report and recommendation of the president to the board directors on a proposed loan to the Republic of Maldives for the Outer Island Electrification (sector)”, (2001), retrieved on July 15, 2011 from: http://www.adb.org/Documents/RRPS/MLD/rrp_32036.pdf.

Jennifer Hinman & Emily Hickey, Modeling and forecasting short-term electricity load using regression analysis, (2009), retrieved on March15, 2012, from: http://www.irps.ilstu.edu/research/documents/LoadForecastingHinman-HickeyFall2009.pdf.

Mrs. J. P. Rothe Dr. A. K., Wadhwani , Dr. Mrs. S. Wadhwani, , Short Term Load Forecasting Using Multi Parameter Regression, (IJCSIS) International Journal of Computer Science and Information Security, Vol6. n2, (2009) 1- 2.

Mohamed, H.K.; El-Debeiky, S.M.; Mahmoud, H.M.; & El Destawy, K.M., Data Mining for Electrical Load Forecasting in Egyptian Electrical Network, in: proceeding IEEE International Conference on Computer Engineering and Systems, Cairo (2006), pp 460-465.

Bunnoon, P.; Chalermyanont, & K.; Limsakul, C., Mid Term Load Forecasting of the Country Using Statistical Methodology: Case study in Thailand, in: proceeding IEEE International Conference on Signal Processing Systems, Singapore, (2009), pp 924-928.

Douglas A. Lind, William G. Marshal & Samuel A.Wathen, Statistical techniques in Business and Economics, 14th edition, Irwin, McGraw – Hill, New York, 2009.


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