| dc.contributor.author | Baqui, Muhammad Niamul | |
| dc.description.abstract | Electricity is vital for U.S. economy. Over the years, the demand and the usage of electricity have skyrocketed, but the electric transmission and distribution processes have been manual. The current work formulates an automated decision-making model for electric-grid resource allocation. Resource allocation is primarily in the form of assigning the best power source to a sink. The model is built in Fuzzy Logic. The input parameters for the model are the power capacity, the price and the distance. A rule base has been created by domain knowledge and analyzing an operator decision making activity. The Mamdani Min-Max approach of is used for defuzzification. A separate model based on Rough Set analysis has also been constructed to compare the results with Fuzzy model. The results obtained from both models show agreement in decision output and reveal the potential application areas of the Fuzzy model. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Fuzzy Decision Model for a Smart Grid | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2012-03-26T21:14:46Z | |
| dc.date.available | 2012-03-26T21:14:46Z | |
| dc.date.issued | 2012 | |
| dc.identifier.uri | http://hdl.handle.net/10365/19396 | |
| dc.subject.lcsh | Smart power grids. | en_US |
| dc.subject.lcsh | Fuzzy logic. | en_US |
| dc.subject.lcsh | Rough sets. | en_US |
| dc.subject.lcsh | Fuzzy decision making. | en_US |
| dc.subject.lcsh | Electric power distribution. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Nygard, Kendall | |
