| dc.contributor.author | Parmar, Viraj | |
| dc.contributor.author | Tulsani, Vijya | |
| dc.contributor.author | Patel, Priya | |
| dc.date.accessioned | 2020-11-12T10:45:43Z | |
| dc.date.available | 2020-11-12T10:45:43Z | |
| dc.date.issued | 2020-07 | |
| dc.identifier.issn | 2231-3990 | |
| dc.identifier.uri | http://ir.paruluniversity.ac.in:8080/xmlui/handle/123456789/7810 | |
| dc.description.abstract | Hybrid Renewable energy systems which combines various energy resources to increase capacity of energy production. The unpredictability of energy demands is a major challenge in Hybrid renewable energy system. To reduce this challenge energy demands should be known in advance which will help to reduce insufficient supply of energy.This paper will focus on how Artificial Intelligence technique can be used in predictability. The Artificial Neural Model is described, as well as Illustration provided about how Artificial Neural Model -ANN model can be trained with certain input parameters, which will process and be able to predict energy demands as an output in advance.The predicted output can then be given to Hybrid Renewable Energy Systemswhich will help increasing the production.This eventually leads to sufficient supply and saving of energy demands. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Alochana Chakra Journal | Volume-9 | Issue-7 | en_US |
| dc.subject | Renewable Energy, Solar Energy, Tidal Energy, Hydal energy, Wind energy, Geothermal Energy. | en_US |
| dc.title | Artificial Intelligence Techniques in Hybrid Renewable Energy Systems | en_US |
| dc.type | Article | en_US |