A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/815253/figures/815253.fig.003a.svgz" name="815253.fig.003a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Original data, noise, and data processed by EEMD at observation site 1</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/815253/figures/815253.fig.003b.svgz" name="815253.fig.003b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Original data, noise, and data processed by EEMD at observation site 2</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/mpe/volume-2015/815253/figures/815253.fig.003c.svgz" name="815253.fig.003c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Original data, noise, and data processed by EEMD at observation site 3</td></tr></table>

<div>Comparison between original data and data processed by EEMD for short-term wind speed data sets collected from three observation sites.</div>

Mathematical Problems in Engineering

fig3

Figure 3

Figure 3: A New Hybrid Model Based on Data Preprocessing and an Intelligent Optimization Algorithm for Electrical Power System Forecasting 