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Long-Term Forecasting of Electrical Energy Using ANN and HSA


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DOI: https://doi.org/10.15866/iremos.v7i3.1618

Abstract


Long term load forecasting is a critical task for the policy makers as well as for the government. A precise upper bound for long term load demand avoids unnecessary power plant investment. This paper presents a hybrid model based on ANN and harmony search algorithm for predicting the electrical energy demand of India for the future years up to 2025. The model requires the per capita GDP and the population as inputs and offers the electrical energy demand as output. The comparison of the results with those of the regression model and ANN demonstrates the effectiveness of the proposed model.
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Keywords


Load Forecasting; Artificial Neural Network; Harmony Search Algorithm

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References


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Data for per capita GDP available at http://www.indexmundi.com/india/gdp_per_capita_ (ppt).html

Data for population available at http://www.populstat.info/Asia/indiac.htm

India’s sector wise energy demand available at http://www.iasri.res.in/agridata/08data%5Cchapter3%5Cdb2008tb3_57.pdf


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