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Application of Local Linear Wavelet Neural Network in Short Term Electric Load Forecasting
| Content Provider | Semantic Scholar |
|---|---|
| Author | Pany, Prasanta Kumar |
| Copyright Year | 2012 |
| Abstract | The electrical deregulated market increases the need for short-term load forecast algorithms in order to assists electrical utilities in activities such as planning , operating and controlling electric energy systems. Methodologies based on regression methods have been widely used with satisfactory results. However, this type of approach has some shortcomings. This paper proposes a shortterm load forecast methodology based on Artificial Intelligence techniques. The work presented in this paper makes use of local linear wavelet neural networks (LLWNN) to find the electric load for a given period, with a certain confidence level. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.ijcaonline.org/archives/volume51/number13/8105-1703?format=pdf |
| Alternate Webpage(s) | http://research.ijcaonline.org/volume51/number13/pxc3881703.pdf |
| Alternate Webpage(s) | http://www.ijcaonline.org/archives/volume51/number13/8105-1703?format=pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Artificial intelligence Artificial neural network Automated planning and scheduling Deregulation Electrical load Gradient descent Load profile Neural Network Simulation Numerical weather prediction Projections and Predictions Wavelet |
| Content Type | Text |
| Resource Type | Article |
