Prediction Modeling for Future Electrical Energy Demand in Malaysia
Accurate forecasting of energy requirement for future development of the country is one of the most important factors of energy management. Adequacy of energy is the main factor for the development of a country. Electricity producing natural resources are depleting very fast, all over the world,...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2006
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/610/1/1600449.pdf |
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| Summary: | Accurate forecasting of energy requirement for future development of the country is
one of the most important factors of energy management. Adequacy of energy is the
main factor for the development of a country. Electricity producing natural resources
are depleting very fast, all over the world, since their quantity is limited and their use is
increasing very rapidly. But the pace of development can not be compromised.
Financial limitations do not permit to, increase the generation capacity to meet the peak
demand and produce surplus electricity after peak hours, and obtain new technologies
of electricity generation. For installation and maintenance of generation capacity,
transmission and distribution infrastructure long term forecasting is very important.
Energy requirement depends on number of variables, some of them which are cardinal
to the energy consumption and addressed here are population, number of electricity
consumers, per capita electricity consumption, peak electricity demand, gross domestic
product and annual electricity consumption of the country. Data for these variables are
available annually and have very firm relation with time. These data were analyzed in
this work. Annual electricity consumption has been taken as dependent and rest as
independent variables. All the variables have been evaluated for first, second and third
order polynomial with time and mathematical relation was found. This mathematical
relation was then extrapolated into future for next ten years, the forecast horizon. Out of
these, evaluated values of independent variables having minimum standard deviation
from the past data trend, were used in developing multi variable model. All the
evaluation work was performed on MATLAB software. The chance of error is low in
this model since it takes the variation of data into consideration and follows the
previous trend by checking standard deviation. Once the data are keyed in the program
it takes less than a minute in giving the forecasted values and its corresponding graph.
The achievement of this work is that by just updating the data of the variables for recent
year in the program the current updated forecast for next ten years can be obtained. This
forecast may be of great use for energy managers. Since it is sensitive to six
independent variables, it gives more reliable forecast. This program can be used for any
country for the same forecast horizon with the assumption that the previous trend will
persist.
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