Abstract
The accurate prediction of annual electricity consumption is crucial in managing energy operations. The neural network (NN) has achieved a lot of achievements in yearly electricity consumption prediction due to its universal approximation property. However, the well-known back-propagation (BP) algorithms for training NN has easily got stuck in local optima. In this paper, we study the weights initialization of NN for the prediction of annual electricity consumption using the Cultural algorithm (CA), and the proposed algorithm is named as NN-CA. The NN-CA was compared to the weights initialization using the other six metaheuristic algorithms as well as the BP. The experiments were conducted on the annual electricity consumption datasets taken from 21 countries. The experimental results showed that the proposed NN-CA achieved more productive and better prediction accuracy than other competitors. This result indicates the possible consequences of the proposed NN-CA in the application of annual electricity consumption prediction.
Highlights
Electricity is a major driving force for economic development in many countries
The experiments aimed to examine the effectiveness of the proposed method for the annual electricity consumption prediction
multilayer neural perceptron (MLP) predicted consumer electricity usage, a method based on metaheuristic algorithms for the weights initialization of an MLP was implemented, as well as to analyze annual electricity consumption
Summary
Electricity is a major driving force for economic development in many countries. The overall demand for power increases continuously, even more, prominent in the future.APEC is the acronym of the Asia-Pacific Economic Cooperation that is a cooperative economic group in the AsiaPacific region. Electricity is a major driving force for economic development in many countries. The overall demand for power increases continuously, even more, prominent in the future. APEC is the acronym of the Asia-Pacific Economic Cooperation that is a cooperative economic group in the AsiaPacific region. The high growth rates in recent decades of APEC results in a significant increase in electricity consumption. APEC energy data has proved essential in tracking energy consumption, reduction, and in determining the group’s renewable energy goals. APEC is committed to improving efficient energy technologies; by setting targets and action plans, thereby creating the necessity to predict future electricity consumption usage accurately
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