The Combination Forecasting of Electricity Price Based on Price Spikes Processing: A Case Study in South Australia

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">ARIMA</td><td align="center">BP</td><td align="center">Kalman</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">MAPE (%)</td><td align="center">26.05</td><td align="center">25.32</td><td align="center">21.12</td></tr><tr><td align="left">RMSE ($/MWh)</td><td align="center">10.62</td><td align="center">9.88</td><td align="center">7.81</td></tr><tr><td align="left">MAE ($/MWh)</td><td align="center">7.93</td><td align="center">7.73</td><td align="center">6.04</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Comparison of three individual forecasting models.

Abstract and Applied Analysis

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Table 3

Table 3: The Combination Forecasting of Electricity Price Based on Price Spikes Processing: A Case Study in South Australia 