Peak Load Forecasting for Vietnam National Power System to 2030

Authors: Nguyen Hoang Minh Vu*, Vo Viet Cuong, Phan Thi Thanh Binh


Gross domestic product (GDP) growth rate, electric power consumption, and maximum load power demand (Pmax) have a closed but complicated and unexplicit correlation. Using the feed-forward back propagation (FFBP) method, a modified model of neural network, this paper will introduce a new long-term prediction approach for the maximum load power of Vietnam. Results from simulation indicate a considerable correlation of three parameters regarding electric power consumption demand, GDP growth rate, and maximum load power demand; the mean error of suggested model is about 1.92%. This is a reasonable range of mean error for a long-term prediction where the correlation of variables is not explicit. According to the basic scenario of National Economic Forecasting Model to 2030, the Vietnam’s GDP annual growth rate is about 7% per year, and the corresponding electric power demands (GWh) are forceated in the previous paper, Pmax in 2020, 2025 and 2030 are forecasted here at 40,332 MW, 60,835 MW, and 87,558 MW, respectively. Those results are 3.4 - 4.2% lower than forecasted values of the Revised National Power Development Plan VII (hereinafter referred to as PDP 7 rev) for the period of 2011-2020 with the vision to 2030.


Forecast, Peak load, Neural network, Feed-forward back propagation - FFBP, Vietnam
Pages : 7-13

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