High potential site identification for hydroelectric power plant by delineating altitude in DEM images and modelling of power generation.

1. Modelling of Run-Of-River
Hydro generation by
Identifying high potential
location using DEM model.
Hariharan Ramalingam
MEng ECE

2. PROBLEM STATEMENT
CAUSES
• Energy generation is one of the most challenging tasks and needs a paradigm shift to a
sustainable source of energy as the conventional source is causing pollution that jeopardizes the
environment and also depleting at a faster pace.
• Hence in order to decarbonize the power generation we need to focus on Clean energy
generation.
REASONS
• Hydropower is better for the environment than other major sources of electrical power, which
use fossil fuels. Hydropower plants do not emit the waste heat and gases—common with fossil-
fuel driven facilities—which are major contributors to air pollution, global warming and acid rain.
• Hydroelectric power generation has an efficiency of nearly 90%.
• Thus, modelling the high potential site and then computing the energy generation could help us
choose the location of installation wisely.
• Also , accurate and reliable power generation forecasting of hydropower is essential for load
scheduling and grid planning.
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3. INTRODUCTION
Definition:
Hydroelectric power plants generate electricity using generators that are driven by turbines that convert the
Kinetic energy of fast flowing water into mechanical energy.
Kinetic Energy ( running water) -> Mechanical Energy (rotation of turbine) -> Electrical Energy (generator)
Types:
• Run- Of- River : Uses the natural flow of river (flow upstream= flow downstream)
• Impoundment: uses a dam to store river water in a reservoir.
• Pumped Storage: has two reservoirs (upper and lower).
3

4. INTRODUCTION
Fundamental working of RoR hydro-electric plant.
Lanes, C. (2021, March 11). Getting off the Grid - Have you considered Hydro-Electric
Power? HubPages.
https://discover.hubpages.com/politics/Getting-off-the-Grid-Have-you-considered-
Hydro-Electric
• Unlike the common impoundment facility, RoR
system does not have any water storage facility
and hence they can’t regulate the water flow,
rather they flow along the natural decline of the
riverbed.
• For a run-of-river system to operate, two
geographical features are required.
• One is a substantial flow of water and the other is
sufficient hydrostatic head to enhance the water’s
energy.
• A greater drop in elevation means more
gravitational force acts upon the water, increasing
its kinetic energy.
• It is important that the river have constant year-
round flow as well. Some systems use a small-scale
dam or weir to ensure that enough water enters
the system.

5. INTRODUCTION
ROR plant advantages:
• Decreased environmental consequences.
• There is no change in the water’s temperature or chemical composition or oxygen levels.
• Lower development cost.
• Flooding does not take place.
ROR plant Disadvantages:
• Power generation capacity is low.
• Unfirm source of power.
• Needs constant water flow.
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6. STUDY AREA
6
Water station locations (Historical Hydrometric Data Map Search - Water Level and Flow
- Environment Canada, n.d.)

7. SITE SELECTED
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8. ASSUMPTIONS
• Hydro Electric power generation period is only from the month of
June to October.
• The water flow at the selected location is same as the data collected
from the nearest station.
• The water flow is constant as the site is located close to an existing
impoundment facility, upstream.
• Turbine efficiency is considered as the overall efficiency.
• Losses were not considered as a part of power calculation.
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9. CONCEPTUAL MODEL
9
Using ArcGIS, delineate
the watershed basins
and add elevation
profile information
To determine the site
with high elevation
profile from the map
created.
To determine the
nearest water office and
to model the water flow
for the selected site
To Calculate the Hydro
electric power
generation:
P= dH* Q* η* g* ρ
Download the
DEM image of the
site location
dH (head
height m)
Q (water
flow m3 /s)
η (efficiency)
g (gravity
m/s2)
ρ (density
of water
kg/m3)
Francis
Turbine
Perform
sensitivity
Analysis
Calibration
Validation

10. Digital Elevation Model
10
Unprocessed DEM
Watershed Delineation
Altitude Delineation

11. CALIBRATION AND VALIDATION
11
y = 4.377x + 64.733
R² = 0.2869
0
50
100
150
200
250
300
350
400
0 50 100 150 200 250 300 350 400
Station
B
Station A
Calibration (1991-2003)
R² = 0.2008
RMSE= 61.09647
0
50
100
150
200
250
300
350
400
0 100 200 300 400
Station
B
Predicted
Station B Observed
Validation (2004-2016)
0
20
40
60
80
100
120
140
160
180
0 50 100 150
OBSERVED
&
PREDICTED
FLOW
DOY
Hydro Graph for the year 2016
B dwnst_obs B dwnst_pred
26 years historic data, considering the months from June- October. The first 13
years has been used for calibration and last 13 years for validation.
R² = 0.2008
RMSE = 61.09647
ENS = 0.206996
Calibration results (1991-2003)
Validation results (2004-2016)
Figure 7. Hydrograph (2016 – June to
October)

12. Calculation of Power Generation
• P= dH* Q* η* g* ρ
• dH- Head, considered as 10m, similar to the site’s elevation.
• Q- flow rate, predicted using historic flow data.
• η- efficiency, considered as
• g- gravity
• ρ- density of water
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η= 90%
0
2
4
6
8
10
12
14
16
01-06-2016 01-07-2016 01-08-2016 01-09-2016 01-10-2016
POWER
GENERATED
(MW)
DAY OF YEAR
Power (2016) vs DOY
P Power gen
0
20
40
60
80
100
120
140
June July August September October
Power
generated
(MW) Months
Average Power vs Month

13. SENSITIVITY ANALYSIS
13
0
5
10
15
20
0 5 10 15
Power
Generated
Axis Title
Change in Efficiency
P ,η =85 P ,η =90 P ,η =95 P ,η =100
0
10
20
30
40
0 2 4 6 8
Power
Generated
Axis Title
Change in Head height
P,dH =10 P,dH =15 P,dH =20 P,dH =25
0
5
10
15
20
0 2 4 6 8 10 12
Power
Generated
Axis Title
Change in Flow rate
Q-20 Q-10 Q Q+10 Q+20 Q+30
Sensitivity analysis of efficiency
Sensitivity analysis of head height
Sensitivity analysis of water flow

14. RESULTS AND DISCUSSION
• The high potential site for RoR Hydro plant installation was
determined and the water flow was predicted with flow data from
nearby water office and the power generation was calculated.
• The month of June is observed to have the highest power generation
as a result of huge mass of snow melt.
• The values of R² , RMSE & ENS could be improved upon gathering
precise flow data.
• From sensitivity analysis it is found that with a higher head (vertical
height) there is a considerable increase in power generation.
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15. Future Scope
• The model would yield better results upon considering other
parameters such as the
• Meteorological data
• Vegetation cover data
• Soil type distribution data
• Geomorphologic data
Also the flow data from point location could help the model to better predict
the outcomes.
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16. REFERENCE
• Linquip, B. (2021). Run-of-the-river Hydroelectricity in Simple Terms. https://www.linquip.com/blog/run-of-the-river-
hydroelectricity/
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Hydroelectric reservoir. (n.d.). https://energyeducation.ca/wiki/index.php?title=Hydroelectric_reservoir&oldid=10245
• Cada, G., Carlson, T., Dauble, D., Hunt, R., Sale, M., & Sommers, G. (n.d.). Hydropower: Setting a Course for Our Energy
Future. Wind and Hydropower Technologies Program (Brochure).
• Zaidi, A. Z., & Khan, M. (2018). Identifying high potential locations for run-of-the-river hydroelectric power
plants using GIS and digital elevation models. In Renewable and Sustainable Energy Reviews (Vol. 89, pp.
106–116). Elsevier Ltd. https://doi.org/10.1016/j.rser.2018.02.025
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