Keywords
decentralized energy, linear programming, energy optimization, gis
Start Date
1-7-2012 12:00 AM
Abstract
GIS can not only improve the way we produce and deliver energy, but can also change the way we view our earth’s resources. In order to provide sustainable energy supplies, humankind is exerting tremendous efforts to secure and cultivate renewable resources, such as wind, solar, geothermal, and biomass energy resources. Using local resources reduces disparity in rural and remote areas in terms of the reliability of supplies and promotes the generation of income. In this research, spatio-temporal analysis in GIS is employed to design decentralized energy systems using renewable energy resources. Spatio-temporal analysis entails estimation and visualization of renewable energy sources on regional and local spatial scales, and optionally in separate periods. GIS organizes spatial data so that case-oriented optimization methods can select the data necessary for specific tasks. Thematic maps are used for data inputs and display of original data and optimization outputs. In addition to spatial methods in GIS, advanced workflows based on linear programming are developed to extend standard routines. Spatio-temporal analysis is employed to design a decentralized system in a selected region of the Czech Republic. The resulting design includes biomass technology, wind turbines, and solar energy systems. The results yield various scenarios based on setting different cost coefficients and constraints. In addition to traditional constraints, such as available land and funds, local restrictions and regional regulations are used to demonstrate other limits that can significantly change the technological and economical parameters. The final map layers can illustrate the total utilization of various energy systems in space and time, which can assist in decision-making processes on local and regional scales.
Spatio-temporal Analysis of Decentralized Energy Systems
GIS can not only improve the way we produce and deliver energy, but can also change the way we view our earth’s resources. In order to provide sustainable energy supplies, humankind is exerting tremendous efforts to secure and cultivate renewable resources, such as wind, solar, geothermal, and biomass energy resources. Using local resources reduces disparity in rural and remote areas in terms of the reliability of supplies and promotes the generation of income. In this research, spatio-temporal analysis in GIS is employed to design decentralized energy systems using renewable energy resources. Spatio-temporal analysis entails estimation and visualization of renewable energy sources on regional and local spatial scales, and optionally in separate periods. GIS organizes spatial data so that case-oriented optimization methods can select the data necessary for specific tasks. Thematic maps are used for data inputs and display of original data and optimization outputs. In addition to spatial methods in GIS, advanced workflows based on linear programming are developed to extend standard routines. Spatio-temporal analysis is employed to design a decentralized system in a selected region of the Czech Republic. The resulting design includes biomass technology, wind turbines, and solar energy systems. The results yield various scenarios based on setting different cost coefficients and constraints. In addition to traditional constraints, such as available land and funds, local restrictions and regional regulations are used to demonstrate other limits that can significantly change the technological and economical parameters. The final map layers can illustrate the total utilization of various energy systems in space and time, which can assist in decision-making processes on local and regional scales.
