1

Feasibility study of Small Hydro Power Plants in Costa Rica

G.Morelli

Zaragoza University

Zaragoza, Spain

Abstract: The CNFL owns several Hydroelectric Power

Plants in the Virilla´s river basin. This study conducts an

analysis of feasibility, focusing on the company’s Small

Hydro Power plants (SHP). Therefore, only plants with

less than 20 MW of installed power are considered here.

The main objective is to optimize energy yield on

existing plants, especially on those which are at the end

of their life cycle.

It is important to mention that many of these plants have

been subject to repowering, addition of new units or just

upgrades, during periods as long as one century.

Keywords: Feasibility, Hydropower, Optimization,

Turbine, Costa Rica, Profitable.

1. INTRODUCTION

For validation of the method National Company of

Electricity of Costa Rica( CNFL) requirements and

previous consultancies have been considered. This is the

case for the feasibility studies of the 12-MW plant

Nuestro Amo and 1-MW plant Ciruelas.

The study aims to achieve the following basic objectives:

Define a Production methodology to predict

optimal possible yield.

Sized optimal equipment and civil works based

on the best cost effective solution.

Apply this methodology on local SHP projects,

previous to move on with costly consultancy.

From a general point of view the study promotes

optimization on aged SHP, by showing that

modernization, repowering or reconstruction works, can

be easily evaluated, are profitable and not as risky as

larger hydro power projects which have long lasting

execution times and higher capital costs.

2. METHODOLOGY

The CNFL has reconstructed several projects, basically

due to flooding damages or just repowered to improve the

low efficiency of aged equipment with high O&M costs.

In order to have a better overview of company

requirements and local market factors previous feasibility

studies from private consultancies will be used as

example exercises to be compared with the feasibility

method described in this work.

Comparing local costs with other trends, will give a good

idea of accuracy of the exercise.

Nowadays the company has installed 10 SHPs. Only 7 of

them are running, while the other 3 are been upgraded or

reconstructed.

Basic selection factors for plants subject to the study for

an upgrading analysis are defined as follows:

a. O&M Costs

b. Turbine Equipment Age

c. Installed power

As higher the O&M costs, older the equipment and

higher the installed power, higher is the priority for an

upgrade. As a result of this assessment, the three SHP

shown in Table 10 have been selected.

Recent ongoing projects have been selected for costs

analysis in orther to compare actualize information. A

new SHP called Ciruelas and an old plant called Nuestro

Amo, which is subject to modernization since Power

House was severely damaged. Also SHP-C, is chosen

from Table 10.

More detailed information is summarized in Table1. In

total 2 SHP for upgrade and 1 SHP for new construction

are subject to analysis under the methodology of this

document.

Table 1. SHP Characteristics.

In order to full fill the objectives, the following

methodology must be completed:

1. Calculation of the available Hydraulic Potential

Ciruelas

(SHP-C)

Nuestro

Amo(SHP-N)

Electriona

(SHP-E)

Study Type - New Upgrade Upgrade

Average Flow Q (m3/s) 0.73 3.60 9.68

Head H (m) 92.00 179.00 79.00

Long (m) 45.00 45.00 30.00

Height(m) 7.00 7.00 10.00

Penstock Long (m) steel 559.00 736.00 100.00

Forebay/weir reservoirVolume (m3) 23,000.00 90,000.00 5,000.00

Canal Long (m) 1,337.00 1,800.00 500.00

Power lines 20KVLong (m) 1,337.00 1,800.00 500.00

Flow Rates Data - Consultancy Consultancy Production

Weir

SHP

Fix

CharacteristicsMeasure

2

2. Definition of an operation mode

3. Optimization of Yield

4. Definition of cost calculation

5. Optimal sizing and selection of the system

6. Investment analysis

2.1 Hydraulic resource

Flow assessment from Consultancy is used for the

Ciruelas and N. Amo plant [2, 3].

For Electriona SHP, no accurate historical flow data was

available, but energy yield information from 10 years

gives valuable data, by applying general formulas as for

Power described in “Equation (27-34)”,as rule of the

thumb a simplify method is used to obtain Power

capacity river flow is obtained.

2.2 Yield optimization

In order to reproduce Energy yield, different parameters

must be established depending mainly on national tariff,

river flow and the size or capacity of the water reservoir.

a-Tariff Scheme: As shown on Table 2, different prices

are set for Energy(Kwh) and for “Firm energy (KW)”,

which is paid for the lowest power measured during the

interval of one month.

Table 2. Tariff Scheme in Costa Rica. (CNFL, 2011)

b-River Flow: Historical data for flow discharge from

“Fig. 3” is assumed to be equal each day of the

corresponding month. As an average value, hourly flow is

used to calculate the most profitable production scheme.

c-Reservoir Volume: Since all of the plants have a small

dam or weir, this reservoir must be taken into account, in

order to improve firm energy, which generates an

important share of total income.

2.3 Operation of the system

In order to get maximum revenues, best turbine flow rate

option is chosen, based on most profitable operation

mode, by selecting the value of remaining water volume

in the reservoir for a 24 h Operation interval. This mean

using water reserved volume to operate in the different

sub-Periods (A till D), mentioned in Table 2.

Finally best combination of each interval revenues will

give optimal economic solution.

Selection of formulas are based on basic concepts of

Flow Mechanics [4], on the principle of conservation of

mass, which can be applied for a theoretical analysis on

weir or forebay reservoir, “Equation (2-16)” is used.

The calculation of monthly income depends on the

parameters mentioned before. For this reason a solution

tool must be used to consider several options. “Solver”

Macro of MS Excel was chosen.

Annex B, shows an example of using of solver based on

defined formulas, daily tariff scheme and techno-

economic analysis.

2.4 Techno-Economical analysis

In order to determine the most cost effective solution,

maximum Profitability Index (PI), is used which is

represented by “Equation (23)”.

PI, is a decision making index which help choosing

between projects with different initial outlay.

NPV is obtained according to calculations described in

Appendix C, and Capital Cost by IDEA(see Annex D)

and upgraded formulas, based on Head (H) and Flow (Q)

[6].

The study focuses on optimal equipment for the local

characteristics, for this reason optimal turbine most must

be selected according to “Fig.1”.

Figure 1, Q-H Diagram. ([7,8]).

Other secondary parameters also must be taken into

account, for example equipment efficiency at variable

flow, and the size of the reservoir. Some examples for

turbine performance can be seen on [8].

Using efficiency curves based on Relative discharge

rates, like shown in “Fig.2”, this simplifies the

optimization of system selection based on profitability,

due the fact that this these curves are can be

approximated with to a polynomial fitting.

Figure 2. Polynomial approximation of turbine η_turb,

for Francis and Ossberger.( [6]).

 PERIOD NOCHE(N.P)

SUB- Period C E B D A

Daily Interval 10:00-12:30 17:30-20:00 6:00-10:00 12:30-17:30 20:00-24:00

/00:00-6:00

# hours 2.5 2.5 4 5 10

$/KWh 0.06

$/KW -

PUNTA(P.P) VALLE(V.P)

0.085 0.07

4.536 4.536

3

2.5 Financial Parameters

In order to obtain NPV, IRR and other financial results

for analysis, the following values in Table 3, are used:

Table 3. Economic Data.

3.DATA ANALYSIS AND DISCUSSION

3.1 Calculation of the available Hydraulic Potential

Since no river information was available for SHP-E,

historical data gives feasible information for further

calculations. Using “Equation (27, 28)”s for power and

energy, with SHP data, nominal output values are

obtained, as a rule of the thumb Operational Availability

(OAV) is considered around 85%, for this method, based

on average values, computations are shown in Annex E.

On the other hand, consultancy`s river flow assessment

was used for Nuestro Amo and Ciruelas. Data is shown in

“Fig.3”.

Figure 3. Monthly Average Flow.

As is expected a clearly dry and wet season is presented

for analysed cases.

Others Factors that must be considered is river`s

contamination and sediment production, like garbage and

sand, that could affect turbine performance, especially on

urban rivers like N.Amo and Electriona.

3.2 Cost Analysis

Project Investments analysis highly depends on cost

analysis, therefore a reliable method must applied.

Different papers presents Cost/KWH or KW based on

SHP Power capacity and Head, as in [9], but the

methodology used form the IDAE based on H and Q, best

fits optimization requirements since operation mode will

depends of relative discharge and on this incomes.

Also Breakdown cost of SHP, are analysed on developing

countries, as in “Fig.7” on Annex A. Electromechanical

range is between 20-50%, the same for civil works, but as

a global analysis any assumption could be made since

costs of Civil works will depends on local conditions.

In order to have an overview between IDAE´s Cost

analysis which is based on European´s costs, basically on

Spanish market, a comparison with local consultancy

studies is done; results are shown in “Fig.4”.

Figure 4. Cost comparison Consultancy vs Theoretical

Graphs in “Fig.4”, shows big differences, from this

analysis it becomes clear that Local Costs take into

account more complex installations with expensive

electromechanical systems like: Fire systems, Gensets,

Automatized gates and Trash racks between others.

Stronger civil works are needed, due to fact that the

country is situated in a volcanic and seismic zone. Also

temporal flooding, typical from tropical locations requires

strength oversizing of dams and weirs.

Additional elements like sediment traps are required at

the beginning (intake) of the canal and at the end of the

canal, before the forebay. Logistic costs must also be

considered. Costs are summarized in Table 4.

Table 4. Installation costs.

4

Other source of actualized information are considered

like International Renewable Energy Agency(IRENA)

reports in [9], from 2012.

For small hydro category according to Irena (see Table

11) ,costs are between acceptable range for Theoretical,

and just above or near the limit for Consultancy.

Theoretical formulas are selected for further analysis.

Since consultancy cost are specific for each particular

study, cost analysis from IDAE presents a validated

method, needed for proposed methodology.

3.3 Optimal sizing and selection of the system based

on profitability

As shown in “Fig.3”, tropical weather presents a variable

range of precipitation and seasonal flows in the rivers.

For this reason, two different types of site configurations

are selected for analysis based on Mixed Type Run of

river.

According to “Fig.1”, which shows Q-H Diagram,

possible turbines will be selected according to each

particular case and comparison will made in order to

choose best technical solution.

.

When apply, the following configurations are compared:

Hourly Reservoir vs. Run of River

Use of Flashboards or Not, above the Weir.

Use of flashboards presents an opportunity to increase

water capacity of the reservoir, which is highly paid

during peak hours, and needed in the dry season.

The use of Flashboards must take into account an

automatic method or fuse gate system, that opens at

excessive water level during inflows, this way water will

not reach high levels upstream and floods will be avoid

on the area.Evaluation asumptions are specify in Table5.

Table 5. Evaluation Assumptions

As mentioned before, the Solver optimization tool, with

operation constraints is used to maximize Energy yield,

taking into account one or more turbines.

Two methods will be used for sizing turbine:

Best IRR( Internal rate of return), for NEW

SHP-C

Best CI (Cost effective Index), for SHP-N and

SHP-C.

IRR, is an optimal method for financial evaluation of

projects, with the disadvantage that many computations

have to be done.

By using optimal CI, a higher income with a lowest

Initial Investment is obtain and less computations are

needed. This the best option for investments from own

capital and considering that SHP can be repower few

times during its lifetime, future sizing of the equipment

will tend to remain as original, as long as hydraulic

resource and equipment present the same tendency.

, but not guarantees best IRR.

3.3.1 New SHP-C

For Sizing of a new plant SHP-C, different Flow rate

values where selected and graph them against IRR with

maximize Incomes obtain by Solver tool, as shown in

“Fig 5,6”.

Figure 5. SHP-C Optimal selection Ossberger Turbine

Figure 6. SHP-C Optimal selection FrancisTurbine

5

By selecting higher IRR, optimal solution is guarantee.

Table 6, is used to summarize results.

Table 6. Optimal selection SHP-C.

3.3.2 Upgrades on SHP-E and SHP-N

Since major investment on upgrades depends on

electromechanical (Turbines, Power Transformers and

Electrical general system); costs of these elements are

used as a reference for sizing the turbines.

In order to simplify the iteration of values and not extend

the present work, the Solver tool, objective cell is based

on maximum Cost effective solution This value will be

called Cost effective Index (CI) and is defined according

to “Equation (16)”.

Since SHP-N presents a 179 m Head, suitable turbines

that could fit are Francis and Pelton, but as mentioned

before trash and sediment is a problem presented on

rivers located in the Virilla´s Basin, for this reason jets

from Pelton turbine can be easily wear down or

obstructed.

Francis is chose as only option, considering the

majoritarian equipment installed in the country

correspond to this kind, and experienced local workshops

are available (see Table7).

Table 7. Optimal selection SHP-N.

Finally results(see table 6,7) shows that Ossberger

presents some advantages over Francis, like production

maximizing especially on dry season, where in most

plants turbine discharge is less than nominal. Also

crossflow turbines are considered being self-cleaning

turbines which can be a benefit due to the reduction of

maintenance stops resulting of trash problems. Crossflow

technology is mostly unexplored on local projects, but the

benefits seem to outweigh the risk.

Table 8. Optimal selection SHP-E.

3.4 Investment analysis

Since CNFL is an utility company that has to buy the

electricity share that is not produced “in house”, selection

for Project priority will be arranged on best PI and

IRR(Internal rate of return),PI analysis considered

Investor share, in this case CNFL`s Investment.

This way a best management of capital is made, by

looking toward for the “biggest bang for the buck”.

In the C.R. different Banks have preference rates and

incentives for Renewable Energies Projects, like risk

guarantees offered by “BCID”(Centro American Bank Of

Developing and Integration) as high as 1 Million $ per

Project, at an annual interest rate of 1.5% [11].

This gives an opportunity to local companies to diversify

investments on different project.

Priority arrangement on studied cases is presented in

Table 9. Clearly the best or most profitable project comes

from upgrades and modernization of SHP, considering

that lifetime of civil works could be as long as 100 years.

Several upgrades could be done during this life cycle.

Table 9. Optimal Project priority selection

As presented in Table 9, the 3 projects are between

acceptable cost thresholds from Irena and requirements

are fulfilled according to assumptions in Table 3.

Optimal

Case

SHP-C

CI:FrancisCII:Fran-

Run-Off

CIII:Ossber

ger

CIV:Oss-

Run-Off

CV: CIV-

Flasboards

Q m3/s 1.70 0.90 1.70 1.00 1.00

# UNITS 1 1 1 1 1

Power KW 1,187.54 628.70 1,187.54 698.55 698.55

MWh/year 4,037.51 3,038.80 4,150.97 3,521.33 3,458.53

Incomes T$ 389.37$ 258.86$ 407.00$ 300.03$ 309.73$

Electro-

mechanic

CostsT$

682.99$ 691.63$ 965.46$ 743.06$ 743.06$

Civil Works

Costs T$3,537.46$ 1,859.65$ 3,356.98$ 1,921.78$ 1,944.28$

Total Costs

T $4,220.45 2,551.28$ 4,322.44 2,664.85$ 2,687.35$

PI 0.85 1.25 0.93 1.75 1.86

IRR 6.2% 7.6% 6.5% 9.1% 9.4%

NPV 2,857.44$ 2,558.14$ 3,217.25$ 3,720.92$ 4,005.60$

Pay Back 17.00 14.00 16.00 12.00 12.00

6

Discount rates of optimal selections are above 7%,

upgrades cases present an excellent payback of less than

1 year and return on investment are as high as 11 up to 14

times, as shows by PI.

For new small SHP-C, PI is not as good as upgraded

projects, but still is a feasible investment.

It is advised to continue further analysis in the

corresponding priority arranged by highest PI order as

described in Table 9.

4. CONCLUSIONS

1. Not using reservoirs decreases initial

investment costs of around 20% and eliminates related

high maintenance costs, due to heavy sedimentation of

local rivers, especially on Virilla`s river basin that is

strongly affected by floods and pollution from the Cities.

2. Investments with Francis and Ossberger

turbine are substantially similar. Main reason for

selection will not be turbine Investment but due to profits

from energy yield and firm energy.

3. It is well known that the use of several turbines

benefits production reliability and minimizes

operational risks. Because a large% of the electricity

income depends on "firm energy" the most viable

strategy is the application of two turbines at least; twin

systems are the most Cost effective alternative.

4. Flashboards do not improve income for SHP-

E and SHP-N. The main reason is the high flow of

Electriona and the large size of the reservoir of SHP-N.

5. SHP-C optimal solution shows that for such

small river flow discharge, best option is avowing,

expensive civil works, and try out some technical

advantages like Crosflow turbines high working range

and lower cost elements like flashboards.

6. Refurbishment and upgrade of SHP

represents a highly profitable opportunity. It is worth

considering these options before and compare results

against new construction, before taking investment

decisions.

5. REFERENCES

[1] ICE, http://www.grupoice.com, 2012, Date of

access: 01/10/2012.

[2] GeoIngenieria, Factibility Study SHP Ciruelas,

2011, Costa Rica: CNFL.

[3] GeoIngenieria, Factibility Study SHP Nuestro

Amo, 2011, Costa Rica:CNFL.

[4] Çengel Y, Boles M, Thermodynamics, 2do Ed.,

1999, Mexico: MacGraw-Hill.

[5] Solver front line systems Inc.,

http://www.solver.com, 2012, Date of access:

01/07/2012.

[6] Taffazzoli A, Bludszuweit H, Market Trends

and Feasibility Study of Small Hydro Power Plant ,

Proccedings of Hydrovision.

[7] ESHA, Guide How de Develop a Small Hydro

Power Plant, 2004, Brussels: ESHA.

[8] IDAE, Small Hydro Power Plant, 2006, Madrid:

IDEA.

[9] IRENA, Renewable energy cost Analysis -

Hydro Power, 2012, Germany: ESHA.

[10] Natural resource Canada, www.nrcan.gc.ca,

2012, Date of access: 01/09/2012.

[11] CEGESTI, Final Report Financial Mechanisms,

Costa Rica, 2011, Costa Rica: OLADE, ONUDI.

6. ACKNOWEDGEMENTSREFERENCES

The author of this paper would like to express his

gratitude and sincere appreciation to the National

Ministry of Science and Technology of Costa Rica for

their support and Hans Bludszuweit for his valuable

comments and suggestions.

7

7. ANNEXES

ANNEX-A:

A1.1 PRIORITY SELECTION MEHOD

CNFL´s Plants Subject to the study where selected based on Identification Electromechanical Equipment Older than 20

years as show in Table 10.

Table 10. Optimal selection SHP-E

Other factor to be taken into account was to obtain O & M Costs of this plants. Also to considered this as a decision

maker. If SHP are over 20 years old, but O & M are on an acceptable range, upgrades intervention could be delay,

according to company judge.

According to Irena, Table 11, a maximum value from Operational Cost could be 4 % of Installation Cost that are around

$1300KW-8000/KW. Is about $52-$320 per KW.

Table 11. Typical Installation Costs[9].

Figure 7. Breakdown Costs on SHP, in developing countries [9].

For this reason 6 years historical data was studied in order to obtain Average Cost of Selected Plants. These are above

or just at that limit; also some SHPs are having red numbers on dry years. This is the case for Electriona and Rio

Segundo which intervention for upgrades is a must. PRI (Priority Index), is used to define which SHP will be selected

first.

(1)

Where:

PRI: Priority index

A: Age

P: Installed Power

1360 1928 84 114

1360 1928 84 114

3105 1991 21 65

1252 1931 81 101

1250 2008 4 9

8001 1991 21 168

250 1908 104 26

1000 1999 13 13

Electriona

Belen

Rio 2do

294 360

278 265

39 376

Priority

Index

Total

Index

O &M

($/KW)SHP

Power

(KW)

Installation

Year Age

8

ANNEX-B: B.1 YIELD ANALISIS FORMULAS

Formulations are made, considering operation of the system under present tariff scheme, in order to find optimal

selection.

(2)

– (3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

where;

(15)

(16)

Where,

VC= Control Volume or System

V2=Initial VC

V1= Final VC

Ven=Volume In

Vsal=Volume Out

Q= Flow

∆t=Time

x: Represents the sub-Period of tariff: A till E .According to the tariff.

x-1: Represents value of sub-period before actual.

Tx: Operational hours on x.

TX*: Relative operational hours

Tn: Sub-period interval in hours

qx: relative turbine flow rate

Qn: nominal flow of turbine

Qx:Rated Flow at sub-period x.

Vx: Total Volume of water at end x.

VTx: volume of water used by the turbine at x.

VRx: Remaining Volume of water at Forebay or Weir reservoir.

VRx*: total remaining Volume of water at end of x.

Tmax: Time lap in hours of x.

Vw: Weir capacity volume

Px: output power

Ex: Energy outpout

effTx: Efficiency of turbine

Qmin: minimum working flow of turbine

qt: Porcentaje of Qn.

K: Efficiency Factor constant

H. Head

CI:Cost Index

Ec: Electromechanic Costs

Ia: Annual Incommes

eff

effTO:T.Ossberger 121.2 -421 444.7 -58.6

effTF:T.Francis 0 -596 238.8 62.08

9

B.2 EXAMPLE TABLES OF ELECTRIONA SHP, YIELD OPTIMIZATION

Example for Electriona describes Cost effective selection for case “C-I: Ossberger”, which determine Turbine Type and

size.

Month days Period

Sub-

period Tmax Tx* Tx Qr Qx Vx VTx VRx* VRx qxx (h) (h) (m3/s) (m3/s) (m3) (m3) (m3) (m3)

1 31 N A 10 0.69 6.93 7.79 11.05 280507 275507 280507 5000 1.00

1 31 V B 4 1.00 4.00 7.79 7.79 112203 112203 5000 5000 0.71

1 31 P C 2.5 1.00 2.50 7.79 8.07 70127 72627 2500 2500 0.73

1 31 V D 5 1.00 5.00 7.79 7.79 140253 140253 2500 2500 0.71

1 31 P E 2.5 1.00 2.50 7.79 8.07 70127 72627 0 0 0.73

2 28 N A 10 0.62 6.16 6.94 11.05 249890 244890 249890 5000 1.00

2 28 V B 4 1.00 4.00 6.94 6.94 99956 99956 5000 5000 0.63

2 28 P C 2.5 1.00 2.50 6.94 7.22 62472 64972 2500 2500 0.65

2 28 V D 5 1.00 5.00 6.94 6.94 124945 124945 2500 2500 0.63

2 28 P E 2.5 1.00 2.50 6.94 7.22 62472 64972 0 0 0.65

3 31 N A 10 0.46 4.58 5.20 11.05 187120 182120 187120 5000 1.00

3 31 V B 4 1.00 4.00 5.20 5.20 74848 74848 5000 5000 0.47

3 31 P C 2.5 1.00 2.50 5.20 5.48 46780 49280 2500 2500 0.50

3 31 V D 5 1.00 5.00 5.20 5.20 93560 93559 2500 2500 0.473 31 P E 2.5 1.00 2.50 5.20 5.48 46780 49280 0 0 0.50

4 30 N A 10 0.34 3.37 3.86 11.05 138917 133917 138917 5000 1.00

4 30 V B 4 1.00 4.00 3.86 3.86 55567 55567 5000 5000 0.35

4 30 P C 2.5 1.00 2.50 3.86 4.14 34729 37229 2500 2500 0.37

4 30 V D 5 1.00 5.00 3.86 3.86 69459 69459 2500 2500 0.35

4 30 P E 2.5 1.00 2.50 3.86 4.14 34729 37229 0 0 0.37

5 31 N A 10 0.58 5.79 6.53 11.05 235195 230195 235195 5000 1.00

5 31 V B 4 1.00 4.00 6.53 6.53 94078 94078 5000 5000 0.59

5 31 P C 2.5 1.00 2.50 6.53 6.81 58799 61299 2500 2500 0.625 31 V D 5 1.00 5.00 6.53 6.53 117597 117597 2500 2500 0.595 31 P E 2.5 1.00 2.50 6.53 6.81 58799 61299 0 0 0.626 30 N A 10 1.00 10.00 11.15 11.05 401549 401549 401549 5000 1.006 30 V B 4 1.00 4.00 11.15 11.05 160620 159123 6497 5000 1.006 30 P C 2.5 1.00 2.50 11.15 11.05 100387 99452 5936 5000 1.006 30 V D 5 1.00 5.00 11.15 11.05 200775 198903 6871 5000 1.006 30 P E 2.5 1.00 2.50 11.15 11.05 100387 99452 5936 5000 1.007 31 N A 10 1.00 10.00 11.19 11.05 402676 402676 402676 5000 1.007 31 V B 4 1.00 4.00 11.19 11.05 161070 159123 6948 5000 1.007 31 P C 2.5 1.00 2.50 11.19 11.05 100669 99452 6217 5000 1.007 31 V D 5 1.00 5.00 11.19 11.05 201338 198903 7435 5000 1.007 31 P E 2.5 1.00 2.50 11.19 11.05 100669 99452 6217 5000 1.008 31 N A 10 1.00 10.00 11.05 11.05 397807 397807 397807 5000 1.008 31 V B 4 1.00 4.00 11.05 11.05 159123 159123 5000 5000 1.008 31 P C 2.5 1.00 2.50 11.05 11.05 99452 99452 5000 5000 1.008 31 V D 5 1.00 5.00 11.05 11.05 198903 198903 5000 5000 1.008 31 P E 2.5 1.00 2.50 11.05 11.05 99452 99452 5000 5000 1.009 30 N A 10 1.00 10.00 12.72 11.05 457928 457928 457928 5000 1.009 30 V B 4 1.00 4.00 12.72 11.05 183171 159123 29049 5000 1.009 30 P C 2.5 1.00 2.50 12.72 11.05 114482 99452 20030 5000 1.009 30 V D 5 1.00 5.00 12.72 11.05 228964 198903 35061 5000 1.009 30 P E 2.5 1.00 2.50 12.72 11.05 114482 99452 20030 5000 1.00

10 31 N A 10 1.00 10.00 13.43 11.05 483525 483525 483525 5000 1.0010 31 V B 4 1.00 4.00 13.43 11.05 193410 159123 39287 5000 1.0010 31 P C 2.5 1.00 2.50 13.43 11.05 120881 99452 26430 5000 1.0010 31 V D 5 1.00 5.00 13.43 11.05 241762 198903 47859 5000 1.0010 31 P E 2.5 1.00 2.50 13.43 11.05 120881 99452 26430 5000 1.0011 30 N A 10 1.00 10.00 14.23 11.05 512420 512420 512420 5000 1.0011 30 V B 4 1.00 4.00 14.23 11.05 204968 159123 50845 5000 1.0011 30 P C 2.5 1.00 2.50 14.23 11.05 128105 99452 33653 5000 1.0011 30 V D 5 1.00 5.00 14.23 11.05 256210 198903 62307 5000 1.0011 30 P E 2.5 1.00 2.50 14.23 11.05 128105 99452 33653 5000 1.0012 31 N A 10 1.00 10.00 12.11 11.05 436113 436113 436113 5000 1.0012 31 V B 4 1.00 4.00 12.11 11.05 174445 159123 20323 5000 1.0012 31 P C 2.5 1.00 2.50 12.11 11.05 109028 99452 14577 5000 1.0012 31 V D 5 1.00 5.00 12.11 11.05 218056 198903 24153 5000 1.0012 31 P E 2.5 1.00 2.50 12.11 11.05 109028 99452 14577 5000 1.00

10

Month days Period

Sub-

period Tmax Tx* effTF effTO Px Ex Pfirm Pfirm Tariff1 Tariff2x (h) (MW) ((MWh)

1 31 N A 10 0.69 0.864 0.860 6.6 1423 62.5

1 31 V B 4 1.00 0.882 0.860 4.7 580 73.5

1 31 P C 2.5 1.00 0.889 0.860 4.8 375 89.5

1 31 V D 5 1.00 0.882 0.860 4.7 724 4.7 4.7 73.5 4751.3

1 31 P E 2.5 1.00 0.889 0.860 4.8 375 4.8 4.8 89.5 4751.3

2 28 N A 10 0.62 0.864 0.860 6.6 1143 62.5

2 28 V B 4 1.00 0.847 0.860 4.2 466 73.5

2 28 P C 2.5 1.00 0.861 0.860 4.3 303 89.5

2 28 V D 5 1.00 0.847 0.860 4.2 583 4.2 4.2 73.5 4751.3

2 28 P E 2.5 1.00 0.861 0.860 4.3 303 4.3 4.3 89.5 4751.3

3 31 N A 10 0.46 0.864 0.860 6.6 941 62.5

3 31 V B 4 1.00 0.701 0.860 3.1 387 73.5

3 31 P C 2.5 1.00 0.732 0.860 3.3 255 89.5

3 31 V D 5 1.00 0.701 0.860 3.1 483 3.1 3.1 73.5 4751.33 31 P E 2.5 1.00 0.732 0.860 3.3 255 3.3 3.3 89.5 4751.3

4 30 N A 10 0.34 0.864 0.860 6.6 669 62.5

4 30 V B 4 1.00 0.000 0.860 2.3 278 73.5

4 30 P C 2.5 1.00 0.553 0.860 2.5 186 89.5

4 30 V D 5 1.00 0.000 0.860 2.3 347 2.3 2.3 73.5 4751.3

4 30 P E 2.5 1.00 0.553 0.860 2.5 186 2.5 2.5 89.5 4751.3

5 31 N A 10 0.58 0.864 0.860 6.6 1189 62.5

5 31 V B 4 1.00 0.823 0.860 3.9 486 73.5

5 31 P C 2.5 1.00 0.840 0.860 4.1 317 89.55 31 V D 5 1.00 0.823 0.860 3.9 607 3.9 3.9 73.5 4751.35 31 P E 2.5 1.00 0.840 0.860 4.1 317 4.1 4.1 89.5 4751.36 30 N A 10 1.00 0.864 0.860 6.6 1989 62.56 30 V B 4 1.00 0.864 0.860 6.6 795 73.56 30 P C 2.5 1.00 0.864 0.860 6.6 497 89.56 30 V D 5 1.00 0.864 0.860 6.6 994 6.6 6.6 73.5 4751.36 30 P E 2.5 1.00 0.864 0.860 6.6 497 6.6 6.6 89.5 4751.37 31 N A 10 1.00 0.864 0.860 6.6 2055 62.57 31 V B 4 1.00 0.864 0.860 6.6 822 73.57 31 P C 2.5 1.00 0.864 0.860 6.6 514 89.57 31 V D 5 1.00 0.864 0.860 6.6 1027 6.6 6.6 73.5 4751.37 31 P E 2.5 1.00 0.864 0.860 6.6 514 6.6 6.6 89.5 4751.38 31 N A 10 1.00 0.864 0.860 6.6 2055 62.58 31 V B 4 1.00 0.864 0.860 6.6 822 73.58 31 P C 2.5 1.00 0.864 0.860 6.6 514 89.58 31 V D 5 1.00 0.864 0.860 6.6 1027 6.6 6.6 73.5 4751.38 31 P E 2.5 1.00 0.864 0.860 6.6 514 6.6 6.6 89.5 4751.39 30 N A 10 1.00 0.864 0.860 6.6 1989 62.59 30 V B 4 1.00 0.864 0.860 6.6 795 73.59 30 P C 2.5 1.00 0.864 0.860 6.6 497 89.59 30 V D 5 1.00 0.864 0.860 6.6 994 6.6 6.6 73.5 4751.39 30 P E 2.5 1.00 0.864 0.860 6.6 497 6.6 6.6 89.5 4751.3

10 31 N A 10 1.00 0.864 0.860 6.6 2055 62.510 31 V B 4 1.00 0.864 0.860 6.6 822 73.510 31 P C 2.5 1.00 0.864 0.860 6.6 514 89.510 31 V D 5 1.00 0.864 0.860 6.6 1027 6.6 6.6 73.5 4751.310 31 P E 2.5 1.00 0.864 0.860 6.6 514 6.6 6.6 89.5 4751.311 30 N A 10 1.00 0.864 0.860 6.6 1989 62.511 30 V B 4 1.00 0.864 0.860 6.6 795 73.511 30 P C 2.5 1.00 0.864 0.860 6.6 497 89.511 30 V D 5 1.00 0.864 0.860 6.6 994 6.6 6.6 73.5 4751.311 30 P E 2.5 1.00 0.864 0.860 6.6 497 6.6 6.6 89.5 4751.312 31 N A 10 1.00 0.864 0.860 6.6 2055 62.512 31 V B 4 1.00 0.864 0.860 6.6 822 73.512 31 P C 2.5 1.00 0.864 0.860 6.6 514 89.512 31 V D 5 1.00 0.864 0.860 6.6 1027 6.6 6.6 73.5 4751.312 31 P E 2.5 1.00 0.864 0.860 6.6 514 6.6 6.6 89.5 4751.3

11

Jan 31 7.79 297.04$ 3,477.37 9.5 251.84 45.2

Feb 28 6.94 243.07$ 2,798.03 8.5 202.71 40.4

Mar 31 5.20 198.65$ 2,319.67 6.4 168.23 30.4

Apr 30 3.86 143.82$ 1,666.57 4.8 121.04 22.8

May 31 6.53 249.30$ 2,915.65 8.0 211.27 38.0

Jun 30 11.15 407.66$ 4,772.42 13.3 344.67 63.0

Jul 31 11.19 419.15$ 4,931.50 13.3 356.16 63.0

Aug 31 11.05 419.15$ 4,931.50 13.3 356.16 63.0

Sep 30 12.72 407.66$ 4,772.42 13.3 344.67 63.0

Oct 31 13.43 419.15$ 4,931.50 13.3 356.16 63.0

Nov 30 14.23 407.66$ 4,772.42 13.3 344.67 63.0

Dec 31 12.11 419.15$ 4,931.50 13.3 356.16 63.0

Total 365 4,031.45$ 47,220.58 130.0 3,413.75 617.7

Income( T$) Energy (MWh)Paid Firm

Power(MW)

Energy

Income

(T$/MWh)

Firm Power

Income

(T$MW)

Month Days Qr (m3/s)

2

2 Ossberger

1.66

11.055,000

79.00

0.70

6628.37Pn: Max Power

Turbine Type

Q mín:Minimum Flow

Qn:Nominal Flow

Vw:Weir m3

H: Head (m)

K: Efficiency factor

Turbine Type

CI 1.17

Ec (T$) 3,454,862.53$

Ia (T$) 4,031,448$

12

ANNEX-C:

C.1 ECONOMIC ANALISIS FORMULAS

Financial most commons tools are used NPV, ROE, PI,

PB and others formulas like Annuities are described as

follow:

(17)

( ) (18)

⁄ (19)

∑

(20)

(21)

ROE=IRR based on Equity (22)

(23)

PB= when i.o=cumulative discounted CF (24)

(25)

(26)

Where:

i: interest rate

PVA: Annuity Present Value factor

Vo: Present Value

A=Annuity

NPV: Net present value, i=to inflation

IRR: Internal rate of return

ROE: Return on equity

CF: Cash Flow

N: Periods of time

i.o: Initial outlay 80% of Direct cost

PI: Profitability Index

PB: Pay Back

N: Period in years

C/KW: Cost per kilowatt

C/KWhy: Specific cost of energy on annual base.

Ea: Annual Energy Yield.(Efficiency loss of 0.5%,

per year is considered due to normal wear of

equipment).

P: Installed power

A: Annuity based on 20 years,i=6.5% and

Vo=Direct Costs

C O&M : Cost of Operation and Maintenance.

C.2 EXAMPLE TABLES OF ELECTRIONA SHP, CASE IV

Example for Electriona SHP describes financial analysis for Case CIV (Ossberger/Flashboards) and comparison

between projects.

6,628 Power Direct Cost

47,220.60 MWh/año 6.5% i

4,038.80$ $/año 10 Period

3.0% Inflation 80% Own Capital

322.42$ O&M (6% of Capital Costs) 20.00% Loan

5,373.69$

General Information

0 1 2 3 4 5 6 7 8 9 10

Income 4,039$ 4,140$ 4,243$ 4,349$ 4,458$ 4,570$ 4,684$ 4,801$ 4,921$ 5,044$

O&M 322$ 332$ 342$ 352$ 363$ 374$ 385$ 397$ 408$ 421$

Net Benefit 3,716$ 3,808$ 3,901$ 3,997$ 4,095$ 4,196$ 4,299$ 4,404$ 4,512$ 4,623$

Refund 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$

BAIT 3,179$ 3,270$ 3,364$ 3,460$ 3,558$ 3,658$ 3,761$ 3,867$ 3,975$ 4,086$

Interest 70$ 63$ 56$ 49$ 42$ 35$ 28$ 21$ 14$ 7$

BAT 3,109$ 3,207$ 3,308$ 3,411$ 3,516$ 3,623$ 3,733$ 3,846$ 3,961$ 4,079$

Net Benefit 3,109$ 3,207$ 3,308$ 3,411$ 3,516$ 3,623$ 3,733$ 3,846$ 3,961$ 4,079$

Refund 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$ 537$

Outlay 4,299 107$ 107$ 107$ 107$ 107$ 107$ 107$ 107$ 107$ 107$

Cash-flow -4,299 3,539$ 3,637$ 3,738$ 3,841$ 3,946$ 4,053$ 4,163$ 4,276$ 4,391$ 4,509$

Cumulative

Cash-flow -4,299 (760)$ 2,877$ 6,615$ 10,456$ 14,402$ 18,455$ 22,618$ 26,894$ 31,285$ 35,794$

13

11 12 13 14 15 16 17 18 19 20

Income 5,170$ 5,299$ 5,432$ 5,568$ 5,707$ 5,849$ 5,996$ 6,146$ 6,299$ 6,457$

O&M 433$ 446$ 460$ 473$ 488$ 502$ 517$ 533$ 549$ 565$

Net Benefit 4,737$ 4,853$ 4,972$ 5,094$ 5,219$ 5,347$ 5,478$ 5,613$ 5,750$ 5,891$

Refund -$ -$ -$ -$ -$ -$ -$

BAIT 4,737$ 4,853$ 4,972$ 5,094$ 5,219$ 5,347$ 5,478$ 5,613$ 5,750$ 5,891$

Interest

BAT 4,737$ 4,853$ 4,972$ 5,094$ 5,219$ 5,347$ 5,478$ 5,613$ 5,750$ 5,891$

Net Benefit 4,737$ 4,853$ 4,972$ 5,094$ 5,219$ 5,347$ 5,478$ 5,613$ 5,750$ 5,891$

Refund -$ -$ -$ -$ -$ -$ -$ -$ -$ -$

Outlay -$ -$ -$ -$ -$ -$ -$ -$

Cash-flow 4,737$ 4,853$ 4,972$ 5,094$ 5,219$ 5,347$ 5,478$ 5,613$ 5,750$ 5,891$

Cumulative

Cash-flow 40,531$ 45,384$ 50,356$ 55,450$ 60,669$ 66,016$ 71,494$ 77,107$ 82,857$ 88,748$

IRR 85.09%

NPV 63,091.37$

PI 14.68$

PB 1

14

ANNEX-D:

D1.1 COST FORMULAS

According to information from Zaragoza University, on-line´s Master in Renewable energy, cost trends are presented

based on IDAE´s work.

15

16

ANNEX-E:

E.1 ENERGY FLOW FORMULAS

General Formulas for hydraulic Power are used, and

adapted with Operational information in order to consider

operational times, and obtain standardized daily average

Flow of corresponding month.

(27)

(28)

⁄ (29)

(30)

(31)

⁄ (32)

(33)

( )

⁄ (34)

Where:

P: output power of the generator(KW)

T: Time interval

E: Energy(KW/h)

OAV: Operational Availability

Hn: Head(m)

: Combined Efficiency of Gen-Turbine

Qturb: Nominal Flow Rate of turbine(m3/s)

AP: Annual Production(KWh/year)

MP: Monthly Production(KWh/month)

AO=Annual Operation Hours(8760 hours)

Fp=Load Factor of the year

OAV: Operational Availability(%)=0.85

M: Monthly % of operation hours(%)

Qi= turbine flow (m3/s) of particular month and

year

Eff: Combined Turbine(86%) and Generator(90%)

Efficiency at Qn= 0.774

DOH: Daily Working Hours(h)

MOH: Monthly working hours(h)

Dm: Days of the month(days)

Qia: Average flow of N years

Qn: Qturb » (m3/h)

E.2 EXAMPLE EXERCISE FOR ELECTRIONAS

Example for Electriona describes year 2011, also is presented Summary Results of 2002-2011 Period.

OAV 84.32

Fp 56.60 Total Year:

Month Days AP OAV MP M MOH DOH Qi

1 31 28,897,780.00 0.84 3,352,900.00 11.6% 56.60 575.28 18.56 10.90

2 28 28,897,780.00 0.84 1,943,200.00 6.7% 56.60 333.41 11.91 8.30

3 31 28,897,780.00 0.84 1,341,600.00 4.6% 56.60 230.19 7.43 5.17

4 30 28,897,780.00 0.84 - 0.0% 56.60 - - -

5 31 28,897,780.00 0.84 138,300.00 0.5% 56.60 23.73 0.77 0.53

6 30 28,897,780.00 0.84 2,610,380.00 9.0% 56.60 447.88 14.93 10.40

7 31 28,897,780.00 0.84 2,659,700.00 9.2% 56.60 456.34 14.72 10.26

8 31 28,897,780.00 0.84 2,643,200.00 9.1% 56.60 453.51 14.63 10.19

9 30 28,897,780.00 0.84 2,723,100.00 9.4% 56.60 467.22 15.57 10.85

10 31 28,897,780.00 0.84 4,067,300.00 14.1% 56.60 697.85 22.51 15.68

11 30 28,897,780.00 0.84 3,481,300.00 12.0% 56.60 597.31 19.91 13.87

12 31 28,897,780.00 0.84 3,936,800.00 13.6% 56.60 675.46 21.79 15.18

28,897,780.00 1.00 4,958.16

2011

Year 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002

Month Qi Qi Qi Qi Qi Qi Qi Qi Qi Qi

1 10.90 6.96 8.13 6.51 5.27 4.96 11.18 8.63 6.31 9.07 7.79

2 8.30 7.56 11.10 4.18 4.24 8.27 8.37 6.78 4.59 6.03 6.94

3 5.17 7.68 8.32 3.25 3.33 5.01 4.26 7.75 2.84 4.36 5.20

4 0.00 6.50 6.07 3.95 3.28 4.05 5.13 4.31 5.28 0.01 3.86

5 0.53 9.73 8.66 7.45 6.81 4.92 6.92 11.10 9.21 0.00 6.53

6 10.40 15.61 12.82 14.74 6.89 9.96 13.60 10.52 16.55 0.44 11.15

7 10.26 15.19 11.59 15.52 8.01 11.40 12.78 8.28 10.63 8.20 11.19

8 10.19 14.74 11.11 15.15 9.41 10.38 11.16 7.91 9.63 10.82 11.05

9 10.85 16.20 7.80 15.65 13.10 12.79 12.76 12.96 12.26 12.84 12.72

10 15.68 14.43 9.06 14.36 13.86 10.65 16.66 13.30 12.39 13.92 13.43

11 13.87 14.49 14.51 15.95 15.12 10.35 15.77 13.99 13.16 15.12 14.23

12 15.18 15.36 8.84 15.62 10.95 10.52 9.23 12.00 13.89 9.55 12.11

Average 9.28 12.04 9.84 11.03 8.36 8.60 10.65 9.79 9.73 7.53 9.68

Qia