Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission
Today, it is very important for developed and developing countries to consume electricity more efficiently. Though developed countries do not want to waste electricity and developing countries cannot waste electricity. This leads to the concept: load forecasting. This paper is written for the short-...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2011-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2011/326763 |
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| author | Sandeep Sachdeva Maninder Singh U. P. Singh Ajat Shatru Arora |
| author_facet | Sandeep Sachdeva Maninder Singh U. P. Singh Ajat Shatru Arora |
| author_sort | Sandeep Sachdeva |
| collection | DOAJ |
| description | Today, it is very important for developed and developing countries to consume electricity more efficiently. Though developed countries do not want to waste electricity and developing countries cannot waste electricity. This leads to the concept: load forecasting. This paper is written for the short-term load forecasting on daily basis, hourly, or half-hourly basis or real time load forecasting. But as we move from daily to hourly basis of load forecasting, the error of load forecasting increases. The analysis of this paper is done on previous year's load data records of an engineering college in India using the concept of fuzzy methods. The analysis has been done on
Mamdani-type membership functions and OFDM (Orthogonal Frequency Division Multiplexing) transmission scheme. To
reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. The error has been reduced to a considerable level in the range of 2-3%. For further reducing the error, Orthogonal Frequency Division Multiplexing (OFDM) can be used with Reed-Solomon (RS) encoding. Further studies are going on with Fuzzy Regression methods to reduce the error more. |
| format | Article |
| id | doaj-art-81f616a7daec472ea06748db7f92a5a4 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-81f616a7daec472ea06748db7f92a5a42025-02-03T07:25:30ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2011-01-01201110.1155/2011/326763326763Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM TransmissionSandeep Sachdeva0Maninder Singh1U. P. Singh2Ajat Shatru Arora3Nims University, Shobha Nagar, Jaipur, Rajasthan 303121, IndiaHaryana Engineering College, Jagadhri, Yamuna Nagar, Haryana 135003, IndiaSeth Jai Parkash Mukand Lal Institute of Engineering and Technology (JMIT), Radaur, Haryana 135133, IndiaSant Longowal Institute of Engineering and Technology (SLIET), Longowal, Sangrur, Punjab 148106, IndiaToday, it is very important for developed and developing countries to consume electricity more efficiently. Though developed countries do not want to waste electricity and developing countries cannot waste electricity. This leads to the concept: load forecasting. This paper is written for the short-term load forecasting on daily basis, hourly, or half-hourly basis or real time load forecasting. But as we move from daily to hourly basis of load forecasting, the error of load forecasting increases. The analysis of this paper is done on previous year's load data records of an engineering college in India using the concept of fuzzy methods. The analysis has been done on Mamdani-type membership functions and OFDM (Orthogonal Frequency Division Multiplexing) transmission scheme. To reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. The error has been reduced to a considerable level in the range of 2-3%. For further reducing the error, Orthogonal Frequency Division Multiplexing (OFDM) can be used with Reed-Solomon (RS) encoding. Further studies are going on with Fuzzy Regression methods to reduce the error more.http://dx.doi.org/10.1155/2011/326763 |
| spellingShingle | Sandeep Sachdeva Maninder Singh U. P. Singh Ajat Shatru Arora Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission Advances in Fuzzy Systems |
| title | Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission |
| title_full | Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission |
| title_fullStr | Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission |
| title_full_unstemmed | Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission |
| title_short | Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission |
| title_sort | efficient load forecasting optimized by fuzzy programming and ofdm transmission |
| url | http://dx.doi.org/10.1155/2011/326763 |
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