TY - CONF
TI - Geospatial Model to Estimate Wind Energy Resource Potential in Remote Locations
AU - Narasimalu, S
AU - Narasimhamurthy, R
AU - Kannan, A
T2 - 2018 ASIAN CONFERENCE ON ENERGY, POWER AND TRANSPORTATION ELECTRIFICATION (ACEPT)
AB - Remote locations in developing regions are experiencing one-fifth energy per capita and heavily depend on fossil fuels. To enhance energy security, all possible renewable energy resources should be exploited. The present state of the art technology demands deployment of wind mast and lidar based infrastructure which is laborious and costly and hence demands preliminary data for justification. This paper discusses a roughness estimation from a geospatial model from which the wind profile and the wind energy density can be estimated. Further spatial and temporal variation help perform macro level techno-economic estimates to identify best wind turbine placement sites and/or wind farm design sites which can be further confirmed by micro-level wind energy site assessment such as wind mast or lidar deployment complimented with computational fluid dynamics model of the terrain.
DA - 2018/10//
PY - 2018
PB - IEEE
UR - https://ieeexplore.ieee.org/document/8610708
LA - English
KW - Wind Energy
KW - Human Dimensions
KW - Marine Spatial Planning
ER -