| Journal Call no. | TA4.C3578 |
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| Author | Pu, Guan-Chih. |
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| Article Title | Neural network based substation short term load forecasting / Guan-Chih Pu and Nanming Chen. |
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| Is Part Of | Journal of the Chinese Institute of Engineers ; v.18, no.3, May 1995, p.333-341, illus. |
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| Abstract | There are many algorithms reported in the literature to forecast the total real load of a power system. But in a power system, the local area loads (both real and reactive loads) are more helpful for dispatching center operators to schedule generation outputs. An approach to substation load (both real and reactive power) forecast by an artificial neural network (ANN) is presented in this paper. Characteristic data of substation load collected continuously by the Supervisory Control and Data Acquisition (SCADA) system of the dispatch center are used for the forecast. To speed up the training process, an adaptive training process of ANN is also applied. This methodology has been applied to substations in the Taiwan Power Company system to forecast both real and reactive loads and the testing results are satisfactory. |
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