Developing a Windfarm Design for the Sundarban Delta
The Sundarban Delta is a world heritage site and its fragile ecosystem is at great risk due to current anthropogenic activities. Habitat fragmentation and setting up of power plants and grids have put the mangrove forests at great risk. To provide a greener, cleaner alternative, we researched into the viability of setting up a wind farm in the delta. The main purpose of the project was to prompt the West Bengal state government to pick up a stalled proposal to do the same by submitting quantitative proof of it's commercial viability.
PROJECT TYPE
Academic
Course: Environmental Impact Assesment
Type: Group Project
GROUP MEMBERS
Sagnick Chatterjee
Ramyani Roy
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MY ROLE
Phase 1 and Phase 3 as
described below
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DURATION
Five Months
November 2018- March 2019
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Phase 1: Analysing Viability of Windfarms from
Wind Climate Maps
Literature review helped us pick 3 promising locations
Input latitude and longitude values of the locations, for ex.:89 degrees north and 21.94 degrees East,
on the DTU wind energy website, obtained .lip files and transformed them into .grd grid files to use of the WAsP 12 software to get wind power tables and windroses
Thus we got probable wind speed in the mapped locations using Weibull curves
Average wind speed was determined to be 5.22 m/s for the delta
Since the average speed met the minimum/ cut in wind speeds for almost all of the wind turbine generators we could explore further into the possibility of building a wind farm in any of these three areas.
Phase 2: Choosing the most efficient wind turbine generator for this particular area
Classified 40 wind turbines based on power density, speed and frequency
Data imported to WAsP Engineering 4 software using Python to get an idea of output power
We calculated available power and applied Betz Limit to get an idea of the actual power that can be obtained from the turbines.
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Cut in Speed
Cut out Speed
We considered the cut out speed and cut in speed of wind required for a turbine (obtained from the power curve) and the hub height to choose the most efficient turbine generator for each location.
Maximum power output was 300-400kW from NEG-Micon NM750-44
Phase 3: Terrain mapping to factor in obstacles
We made a ground level elevation map with Google Earth’s path profile tool, and by calculation of percent slope
WAsP Map
Editor
Mesh grid
Terrain Surface
Geo Projection
Geo Projection Transformer
Using WAsP12 we got obstacle group maps and this helped us visualise ground level elevation, trees, man made network towers, etc. and helped us avoid the obstacles to identify a 50 metre square area that was extremely suitable for setting up a wind farm..
To further bolster our petition, our professor is currently working to take into account the damage that a wind turbine may face in its lifetime, impact on and by anthropogenic factors and calculate the minimum optimum distance between windmills, the number of windmills that can be setup in that area.