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Year : 2011 | Volume
: 1
| Issue : 1 | Page : 24-30 |
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Short-Term Load Forecasting in Deregulated Electricity Markets using Fuzzy Approach
SK Aggarwal1, Manoj Kumar2, LM Saini3, Ashwani Kumar3
1 Electrical Engineering Department, M.M. Engineering College, Mullana, India 2 H.V.P.N. Ltd, Kurukshetra, India 3 Electrical Engineering Department, NIT, Kurukshetra, India
Correspondence Address:
S K Aggarwal Electrical Engineering Department, M.M. Engineering College, Mullana India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/0976-8580.74559
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In this article, a fuzzy inference-based method for short-term load forecasting has been presented. Load data from European Energy Exchange has been selected for the case study. The "time," "temperature," and "historical load" are taken as inputs for the fuzzy logic controller and the "forecast load" is the output. Each of the input variables "time" and "temperature" has been divided into 7 triangular membership functions, whereas the input variable "historical load" has been divided into 10 triangular membership functions. The "forecast load" as output has been divided into 10 triangular membership functions. Then, 1 day ahead load forecast for each hourly interval has been performed using fuzzy logic method. Furthermore, performance of the fuzzy logic model is compared with a conventional model. It has been shown that the proposed method possesses better forecasting abilities than the other model. |
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