Short Term GA-NFIS based Hybrid Method for Prediction of Wind Speed & Power in Sustainable Power Generation
Vijay Kumar1, Yash Pal2, Madan Mohan Tripathi3

1Mr. V Kumar, National Institute of Technology, Kurukshetra, (Haryana), India.
2Dr. Yash Pal, Professor, EED, National Institute of Technology, Kurukshetra (Haryana), India.
3Dr. Madan Mohan Tripathi, Professor, EDD, Delhi Technological University, (New Delhi), India.
Manuscript received on 27 March 2019 | Revised Manuscript received on 08 April 2019 | Manuscript Published on 18 April 2019 | PP: 917-922 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03870376S19/2019©BEIESP
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Abstract: Additional power requirement and integration of non conventional energy sources for power generation into smart grid, forced the world power generating company to divert their attention towards power generation from renewable sources along with conventional sources. Today power demand in different sectors are increasing with continuous increasing population, so it is very challenging task for power generating company to maintain balance between supply and demand. The countries that consume more energy per capita are supposed to have better social- economical status and living standard. Currently power generation from the conventional sources faces many challenges such as environment pollution, continuous availability, storage and security; to mitigate the above problems power generation from renewable sources may be better alternative. So, many countries started power generation from renewable sources such as wind power and solar power by expanding major portion of their energy fund into development of the renewable setup for power generation. In India currently wind power contribution in renewable power sources is very high so, wind may be a better solution for power generation. Power generation from wind puts many barriers in term of intermittent nature, frequency and availability at all places with certain speed that is able to power generation from wind mills. Although above challenge cannot eliminate completely, but it can be minimize with the help of correct prediction technique / method that have accuracy up to certain level which will be acceptable for power generation. In this work GA- NFIS is used for forecasting of wind power and data is collected from Indian wind power sector mills. Results of proposed method are compared with some available soft computing methods such as NARX, SVM-NARX.
Keywords: Prediction, Wind Power, Genetic Algorithm, Neuro- Fuzzy Inference System, Speed Prediction, Absolute Percentage Error (APE).
Scope of the Article: Next Generation Internet & Web Architectures