Tangible benefits of technological prospection and prefeasibility studies in SHP projects Ing. Sergio Armando Trelles Jasso

5 th and 6 th December 2012, Panama City, Panama Tangible benefits of technological prospection and prefeasibility studies in SHP projects Ing. Sergio Armando Trelles Jasso

Agenda Artisanal vs Technological approach to rivers as a source of wealth and well-being Technological panoply Economic impact of advanced technology Conclusions

Artisanal versus Technological approach Gambusino, 1850 Remote sensing, 2012

SHP Project Development Process Promotion Feasibility Optimized Prospection Design Construction Operation Operation Operation

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

Distributed Hydrologic Modeling River Basin : 34,398 km 2 3,334 RHHU Mean RHHU : 10.3 km 2

Distributed hydrologic modeling PET Rain Snow AET 1,2, 3 Z 2 Z 1 Infiltration Q 1-2 θ 1 θ 2 Q direct Q retarded Overland flow Stream network and reservoirs routing Q Z 3 Q 2-3 Q base t θ 3 Slope PET = Potential Evapotranspiration AET = Actual Evapotranspiration Vertical Water Balance in Three Layers Five main calibration parameters

Distributed hydrologic modeling Precipitation (mm) Temperature (c ) Runoff (m 3 /s) Measured Simulated Calibration criteria over wet and dry years period Nash-Sutcliffe Efficiency Volume Difference (%)

Physiographic analysis Output Input Digital elevation model (DEM) Vector map of stream network outlet and water bodies Land use map Soil texture map Nodes Stream network reaches Water bodies Special points Relatively homogeneous hydrologic units (RHHU) Water divide Elevations Slopes Flow directions Percent of land use classes per RHHU Predominant soil texture per RHHU Hydraulic properties of soil

Digital elevation model Resolution: ASTER 30 m INEGI 50 m SRTM3 90 m...

Homogeneous Stream Network 3,284 stream reaches Mean reach length: 3.5 km

Relatively homogeneous hydrologic units

Land Use map 19 Classes

Soil Texture map Hydrodynamic parameters 12 Classes, from Edafology

Meteorological Daily Series 99 Stations Rainfall Maximum Temperature Minimum Temperature Time series of 10 to 30 years

Hydrometric Daily Series 5 Stations Time series of 3 to 5 years 10077 10119 10100 10063 10066

Hydrological model calibration Calibration period: 5 to 7 wet/dry years Simulation period: 20 to 30 years with meteorology Nash-Sutcliffe Efficiency: 0.30 to 0.95 Volume Difference: -5% to +5%

Extended simulation Multiannual daily runoff series of 20-30 years

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

Flow Duration Curve Penstock upstream point Q p Project flow F Q Selected frequency of exceedance Specific at any point along stream network

Daily runoff series Time series Normal series

Monthly runoff Time series Normal series

Long mean annual runoff series Uncertainty of new gauging station Wet or dry year? Increasing or decreasing trend? High impact on economy of project Plant capacity design Income estimation for energy auctions

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

Geospatial Analyses Exclusion Analysis Protected Natural Areas Archaeological Zones Urban zones Irrigation zones Problem areas Distance Analysis Roads and railroads Electric grid Power plants Electric substations Populated places Programmed procedures Annotation in a spreadsheet

Geospatial Analyses

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

SHP project location optimization Min Power, Min Slope, Max Length, Max Flat Distance

Location Municipality State Watershed River Project Query Topology Project ID RHHU ID Stream reach ID Nodes ID Characteristics Intake (x,y,z) Tailwater (x,y,z) Drainage area Mean precipitation Mean flow Flow Duration Curve Design flow at selected frequency Penstock length Hydraulic head Mean slope Power Power/Length ratio Project class Distances Land restrictions Feasibility

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

Project 3D modeling 3D Terrain Contour lines DEM Layout selection Intake location Tailwater location River bank selection Run of river or reservoir Dam height Conduit type and shape Canal Pipe Tunnel Bridge Penstock Dam type and shape Earthfill Rockfill Concrete RCC Arch... Project geometry Lengths Widths Heights Slopes Areas Volumes

3D Terrain preparation

Water intake and tailwater location Intake Tailwater

Water intake and tailwater location Tailwater Intake

River bank selection

River bank selection Bridge/Pipe Tunnel Canal Penstock Right bank

River bank selection Tunnel Canal Penstock Left bank

River bank selection Tunnel Bridge/Pipe Tunnel Canal Penstock Right/Left bank

River bank selection Conduit Left Right Right/Left bank bank bank Canal 1,168 765 799 Pipe 86 148 Tunnel 764 864 578 Bridge 85 148 Total 1,932 1,715 1,525 Penstock 249 215 249 Length (m)

Reservoir characteristics

Dam site characteristics

Dam type and shape Embankment 20,576,704 m 3

Dam type and shape Gravity - Concrete 4,537,156 m 3

Dam type and shape Gravity RCC Straight 3,276,270 m 3

Dam type and shape Gravity - RCC Curved 3,511,158 m 3

Dam type and shape Double Arch 759,967 m 3

Technological panoply Distributed hydrological modeling Time series analysis Geospatial analysis Project location optimization Project 3D modeling Preliminary design optimization

Preliminary design optimization Estimated costs Decision variables Design flow Reservoir capacity Conduits capacity Turbines capacity Project geometry Parametric costs Estimated benefits Energy income Capacity income Carbon credits Financial criteria Cost/Benefit IRR NPV LCOE Payback period

Preliminary design optimization Decision variables Design flow Reservoir capacity Conduits capacity Turbines capacity Other criteria Economic Flood control Water supply Irrigation Fisheries Tourism Real estate Demand for services and industrial goods Regional development Environmental GHG reduction Fuel conservation Inundated land Ecological flow Fish migration Forest cover Water quality Social Electrification People relocation Job creation Community benefits National security

Preliminary design optimization

Prefeasibility study Costs Estimates SHP project Layout Initial turbine selection Civil works pre design Parametric cost formulae Pre Feasibility tools Benefits Estimates Long term daily simulation with flows of Water, Energy and Money Financial Model Economic indicators Decision making Cash Flow

Improved Investment Decisions Detection of prospects Artisanal prospection Technological Prospection Random, Partial, Slow, Costly, Uncertain Systematic, Exhaustive, Effiicent, Reliable

Improved investment decisions Viablity of prospects Artisanal prospection Technological Prospection 3/10 Rate of Success 7/10

Improved investment decisions Dimension of project Artisanal prospection Technological Prospection ±50% Probable Error ±10%

Economic impact of advanced technology in five years... Criteria Artisanal Technological Prospection and prefeasibility losses (MUSD) 1.2 0 Completed projects and installed capacity (n, MW) 10 de 15 20 de 20 Global installed capacity (MW) 150 400 Hydrologic uncertainty 20% 5% Development process duration (months) 30 24 Recovery of investment period (years) 8.4 7.7 Levelized cost of energy (USD/MWh) 53.5 46.3 Cost of projects promotion phase (%) 100 80 Cost of projects design and construction (%) 100 90 Economic Internal Rate of Return (%) 10.1 13.2 Global Net Present Value (MUSD) 68.9 403.3

Expected NPV of SHP projects in five years... 69 403 (MUSD)

The Map of the Treasure

Conclusions It is vital to know water resources time and space variability for SHP site selection and plant design. Surface hydrology and water resources management are complex and most countries lack of maps of SHP potential. Some countries have carried and published SHP assessments with simplified and unreliable hydrologic methods. Prospection and prefeasibility phases are often long, costly and largely uncertain, yet fundamental. SHP development applying advanced technology and global datasets speeds up the process and leads to increased tangible benefits. Experiences gained are replicable at project, river basin or country scale, with great benefit in Latin American countries.

5 th and 6 th December 2012, Panama City, Panama Gracias! Ing. Sergio Armando Trelles Jasso Tulipán Italiano 22, Col. Tulipanes 62388 Cuernavaca, Morelos, México +52 777 322 2945 +52 777 148 2041 Celular atrelles10@gmail.com Skype: atrelles1