dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | West Paraná State University – UNIOESTE | |
dc.date.accessioned | 2018-12-11T17:25:55Z | |
dc.date.available | 2018-12-11T17:25:55Z | |
dc.date.created | 2018-12-11T17:25:55Z | |
dc.date.issued | 2016-06-01 | |
dc.identifier | International Transactions on Electrical Energy Systems, v. 26, n. 6, p. 1339-1357, 2016. | |
dc.identifier | 2050-7038 | |
dc.identifier | http://hdl.handle.net/11449/177543 | |
dc.identifier | 10.1002/etep.2151 | |
dc.identifier | 2-s2.0-84944400190 | |
dc.description.abstract | A grid-based simulation method to forecast the spatial growth of load density in a distribution utility service zone is presented. The future load density is simulated considering a city's dynamic growth. A power-law distribution with fractal exponent is used to determine how much the load density will increase/decrease depending on different factors like: natural growth following patterns, spontaneous new loads without predefined patterns, and urban poles growth that attract/repel new consumers. These factors are simulated using two modules that exchange information. The final result will display a map with future load density considering a heterogeneous distribution, which is the main contribution of this work. The method is tested on a real distribution system in a medium-sized Brazilian city. The most important characteristic of this method is its high efficiency in spatial load density recognition with less input data than traditional spatial load forecasting methodologies. Copyright © 2015 John Wiley & Sons, Ltd. | |
dc.language | eng | |
dc.relation | International Transactions on Electrical Energy Systems | |
dc.relation | 0,453 | |
dc.rights | Acesso restrito | |
dc.source | Scopus | |
dc.subject | electric energy distribution system expansion planning | |
dc.subject | fractal geometry | |
dc.subject | spatial error analysis | |
dc.subject | spatial load forecasting | |
dc.subject | urban dynamics | |
dc.title | Grid-based simulation method for spatial electric load forecasting using power-law distribution with fractal exponent | |
dc.type | Artículos de revistas | |