Development of a spatial load-forecasting module for optimizing planning of electricity supply


Abstract:

In today's economy, there is a strong need to forecast and predict future load demands in order to estimate the amount of load required and to properly prepare the planning purposes. This paper presents the development of a module with the ability to calculate the spatial load forecasting in any area of study. First, the electrical distribution system must be defined with all its components. After a model of geographical and temporal prediction of this demand for electricity, which uses a Hybrid method is developed. The software Python and ARCMAP are used in order to program the module. Furthermore, the developed module considers the main requirements for a good spatial load forecasting. Land use is a key factor in this work, excluding specific areas where is not possible to have growth.

Año de publicación:

2017

Keywords:

  • Spatial Load Forecasting
  • GIS
  • Python.
  • Smart planning

Fuente:

googlegoogle
scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Ingeniería energética
  • Energía
  • Energía

Áreas temáticas de Dewey:

  • Física aplicada
  • Economía de la tierra y la energía
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 7: Energía asequible y no contaminante
  • ODS 11: Ciudades y comunidades sostenibles
  • ODS 9: Industria, innovación e infraestructura
Procesado con IAProcesado con IA