Short-Term Load Forecasting Based on Improved Grey Prediction Approach
碩士 === 國立臺北科技大學 === 自動化科技研究所 === 99 === Load forecasting is widely used by power utilities to predict the amount of power needed to supply the demand. It is very important for the power system operation. A novel approach based on grey prediction models for short term load forecasting was proposed in...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/3hrr78 |
| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 99 === Load forecasting is widely used by power utilities to predict the amount of power needed to supply the demand. It is very important for the power system operation. A novel approach based on grey prediction models for short term load forecasting was proposed in this thesis. To verify the effectiveness of the proposed approach, an experiment was conducted to make a comparison with some commonly used methods including time series, artificial neural networks, and grey prediction models. Data set used in this experiment was adopted from a practical substation of Taipower. Experimental results showed that the proposed approach is promising as it can improve the prediction accuracy of load forecasting by reducing the errors inherent from original grey prediction models.
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