FORECASTING INDUSTRIAL/COMMERCIAL ELECTRICITY CONSUMPTION USING THE LOGISTIC MODEL (Case study of the Electricity Company of Ghana Limited)
| dc.contributor.author | Adotey, Emile Kpakpo | |
| dc.date.accessioned | 2014-01-09T16:32:04Z | |
| dc.date.accessioned | 2023-04-20T01:43:04Z | |
| dc.date.available | 2014-01-09T16:32:04Z | |
| dc.date.available | 2023-04-20T01:43:04Z | |
| dc.date.issued | 2013-06-09 | |
| dc.description | A Thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirements for the degree of [MSc. INDUSTRIAL MATHEMATICS] [June, 2013] | en_US |
| dc.description.abstract | This thesis presents an electricity forecasting model based on the Logistic equation. The proposed model is applied to electricity consumption data of only industrial and commercial consumers. This data is obtained from an Automatic Meter Reading (AMR) system implemented by the Electricity Company of Ghana Limited. The system enables the company to read the meters of industrial and commercial customers remotely without having to send a meter reader to the customer‟s premises. As a result of the implementation of the AMR system, the Electricity Company of Ghana Limited has the capacity to feed enormous amount of energy consumption data into a central AMR database at the head office. The development of the model involved using the analytical solution of the Logistic differential equation. The solution curve has monthly energy consumption as the dependent variable and time as the independent variable. The parameters in the solution curve are computed using linear regression analysis. This is done by fitting the linear form of the solution to historical electricity consumption data. The carrying capacity of the Logistic equation which is referred to as optimal asymptote in this thesis is computed using Fibonacci Search Technique. The optimal asymptote and the parameters that are computed are further substituted into the solution curve of the Logistic equation. This final solution is then used to compute future consumptions. Finally the model was applied and a comparison made between forecast consumption and historical consumption to establish the validity of the model. | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/5507 | |
| dc.language.iso | en | en_US |
| dc.title | FORECASTING INDUSTRIAL/COMMERCIAL ELECTRICITY CONSUMPTION USING THE LOGISTIC MODEL (Case study of the Electricity Company of Ghana Limited) | en_US |
| dc.type | Thesis | en_US |
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