HYDRO 2013 Full Paper

8/18/2019 HYDRO 2013 Full Paper

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Quantifying the Operation and Availability ofSmall Hydro Power Plants

Panagiotis Bourbourakis

PPC Renewables SA

3, Kapodistriou Str. PO 15343

Agia Paraskevi – Greece

IntroductionFor the safe and optimal operation of an industrial plant, man-machine cooperation is an essential precondition. The

aforementioned principle is of utmost importance for Renewable Energy Sources Power Plants, since the application

of reliable and valid monitoring methods leads to minimization of failures and to lifetime prolongment of the plant,

as well as to maximization of the availability and the expected profit.

The monitoring of operation of the Small Hydroelectric Power Plants of PPC Renewables S.A. (16 power plants and

76 ΜW in total), is enabled through dedicated software, which is also android mobile phone operated. The analyzing

methodology combines data from the specifically developed software, from the scada software of the plants and

from the on-site personnel. All trips and out-of-order events are recorded on the basis of parameters such as “date”,“plant serial number”, “unit serial number”, “cause”, etc. After archiving procedure, further process is done by

drawing up data sheets and tables, by making conclusions and by setting up the next necessary steps for preventing

future failure events and achieving optimization of hydro power plants operation.

1. Monitoring the Operation of the Hydro Power Plants.The “PanOpticum DPS” dedicated software is feeded with data transmitted by on-site appliances (in each power

plant), via any available infrastructure (GPRS, satellite internet, etc). Thus we are enabled to real-time monitor the

active power, the grid circuit breaker status and the unit circuit breaker status on each hydro power plant.

Fig.1 Snapshot of the dedicated software, with all power plants in operation.



2. Quantifying the Availability of the Hydro Power Plants.All trips occurring on each unit and each power plant are archived according to the following parameters:

• Trip Monthly Serial Number (e.g. 4, 36, 65).

• Date of occurrence (e.g. 13 August).

• Trip Daily Serial Number (e.g. 4th trip for the 13th of August).

• Small Hydro Power Plant of occurrence (e.g. SHPP Louros).

•

Trip Daily Serial Number for each SHPP (e.g. 5th

trip for SHPP Papadia).• Unit Serial Number of each trip occurrence (e.g. 2 nd trip on Unit 1).

• Trip Cause (Mechanical – Electrical – Electronical – Grid – General - Operations).

• Start – Stop – Duration of each trip.

After recording and archiving of the trips, processing takes place (drawing up charts, making conclusions, service

scheduling, etc). The availability analysis refers to July 2013, while the present methodology has been originally

applied for the last 2 years.

The following table includes the outage hours of each power plant and the occurring availability. The term “specific

outage hours” is introduced due to the reduction of the several plant units in the scale of each single power plant.

Outages due to non-human causes (e.g. insufficient river flow) are not included.

S/N SHPP

Total Monthly

Outage Hours

Specific Total Monthly

Outage Hours

Monthly

Availability(month of 31x24=744hr) (month of 31x24=744hr) (%)

1 Agia Varvara 24,18 24,18 96,75

2 Agios Ioannis 744,00 744,00 0,00

3 Almyros 511,18 511,18 31,29

4 Vermio 7,23 7,23 99,03

5 Gkiona 0,00 0,00 100,00

6 Glafkos 0,00 0,00 100,00

7 Louros 199,95 49,99 93,28

8 Makrochori 0,00 0,00 100,00

9 Oinoussa 0,00 0,00 100,00

10 Papadia 8,70 8,70 98,8311 Smokovo 3,29 2,23 99,70

12 Stratos 31,62 17,22 97,69

13 Alatopetra 0,00 0,00 100,00

14 Vorino 3,17 3,17 99,57

15 Gitani 1,42 0,71 99,90

16 Eleoussa 20,97 10,48 98,59

Total 1555,71 1379,09 87,17

However, the above calculation method does not take into account the installed operating power capacity of each

power plant. Therefore, the term “Specific Availability” is introduced.



S/N SHPP

Monthly

Availability

(%)

Operating Power

(MW)

Weighting

Factor

Specific Monthly

Availability

(%)

1 Agia Varvara 96,75 0,9 0,012186865 1,18

2 Agios Ioannis 0,00 0,3 0,004062288 0,00

3 Almyros 31,29 0,3 0,004062288 0,13

4 Vermio 99,03 0,7 0,009478673 0,94

5 Gkiona 100,00 8,5 0,115098172 11,51

6 Glafkos 100,00 3,7 0,050101557 5,01

7 Louros 93,28 10,3 0,139471903 13,01

8 Makrochori 100,00 10,8 0,146242383 14,62

9 Oinoussa 100,00 1,5 0,020311442 2,03

10 Papadia 98,83 0,5 0,006770481 0,67

11 Smokovo 99,70 10,4 0,140825999 14,04

12 Stratos 97,69 6,3 0,085308057 8,33

13 Alatopetra 100,00 4,95 0,067027759 6,70

14 Vorino 99,57 3,9 0,052809749 5,26

15 Gitani 99,90 4,2 0,056872038 5,68

16 Eleoussa 98,59 6,6 0,089370345 8,81

Total 87,17 73,85 1 97,93

As depicted above, the specific total availability rises up to 97,93%.

The specific outage hours for each power plant are depicted on the following table.

S/N SHPP

Specific Total

Monthly

Outage Hours

(month of

31x24=744hr)

Weighting

Factor

Specific

Weighted

Total Monthly

Outage Hours

Specific Weighted

Outage Hours

Distribution

(%)

1 Agia Varvara 24,18 0,012186865 0,29 0,32

2 Agios Ioannis 744,00 0,004062288 3,02 3,26

3 Almyros 511,18 0,004062288 2,08 2,24

4 Vermio 7,23 0,009478673 0,07 0,07

5 Gkiona 0,00 0,115098172 0,00 0,00

6 Glafkos 0,00 0,050101557 0,00 0,00

7 Louros 49,99 0,139471903 6,97 7,52

8 Makrochori 0,00 0,146242383 0,00 0,00

9 Oinoussa 0,00 0,020311442 0,00 0,00

10 Papadia 8,70 0,006770481 0,06 0,06

11 Smokovo 2,23 0,140825999 0,31 0,34

12 Stratos 17,22 0,085308057 1,47 1,58

13 Alatopetra 0,00 0,067027759 0,00 0,00

14 Vorino 3,17 0,052809749 0,17 0,18

15 Gitani 0,71 0,056872038 0,04 0,04

16 Eleoussa 10,48 0,089370345 0,94 1,01

Total 1379,09 1 15,42 16,63



The following table shows the origination of the monthly outages.

S/NTechnical

Origination

Total Monthly

Outage Hours

(month of 31x24=744hr)

Outage Cause

(%)

1 Mechanical 760,00 48,85

2 Electrical 8,52 0,55

3 Electronical 1,97 0,134 General 5,60 0,36

5 Grid 21,72 1,40

6 Operations 757,90 48,72

Total 1555,71 100,00

The following chart shows the monthly trip frequency, i.e. the number of days (of July 2013), on the basis of the

number of the trips occurring on each day. As depicted, the monthly distribution tends to be normal.

Fig.2 Chart of the monthly trip frequency distribution

The following chart shows the monthly distribution for the daily outage hours, i.e. the total number of specific

outage hours for each day. As depicted, the monthly distribution tends to be inverse normal.

Fig.3 Chart of the daily outage hours distribution

It is to be noted that, for the creation of the above charts, the trip numbers and the outage hours for two (2) SHPPs

were excluded, since they were under reconstruction works and therefore temporarily out or operation.



3. Quantifying the Operation of the Hydro Power Plants.The specific O&M Cost for each power plant has been calculated based on the contractual price for the O&M

personnel and the technical features of each plant (power capacity, annual energy output, years of operation).

S/N SHPP OperationalPower Capacity

(MW)

Mean AnnualEnergy Output

(MWh)

Specific AnnualO&M Cost

(€/MWxMWh)

Years ofOperation

(yr)

Specific Annual Cost

and Years ofOperation

(€/MWxMWh/yr)

1 Agia Varvara 0,9 5.030 9,9 6 1,654

2 Agios Ioannis 0,3 350 0,0 60 0,000

3 Almyros 0,3 600 482,6 59 8,180

4 Vermio 0,7 4.660 131,9 60 2,198

5 Gkiona 8,5 38.020 1,3 26 0,052

6 Glafkos 3,7 11.010 10,9 16 0,682

7 Louros 10,3 44.280 1,5 55 0,028

8 Makrochori 10,8 33.780 1,2 21 0,056

9 Oinoussa 1,5 3.840 6,1 9 0,675

10 Papadia 0,5 2.270 39,6 3 13,216

11 Smokovo 10,4 11.150 0,2 4 0,054

12 Stratos 6,3 11.070 0,4 24 0,015

13 Alatopetra 4,95 14.510 1,1 1 1,114

14 Vorino 4,1 25.120 1,7 6 0,283

15 Gitani 4,2 14.420 2,6 7 0,366

16 Eleoussa 6,6 28.520 0,9 5 0,181

Total 74,05 248.630,00 stdev 0,70659

avg 0,61184

avg/stdev 0,866

As depicted above:

• Despite the vast variation (manned/unmanned - automatic/manual operation, etc) of the operational status of the

power plants, a relative uniformity is to be observed at the Specific O&M Cost, excluding the extreme values

highlighted with yellow color. However, the quantification of quality characteristics for the above mentioned

operational status is not easily feasible.

• Taking into account the years of operation of each power plant, the Specific Cost can be further developed. By

excluding one pair of extreme values at each end of the distribution (as highlighted with green color), it is to be

observed that the standard deviation (0.70659) of the values varies very little compared to the average

(0.61184), i.e. the average is at the 86.6% of the standard deviation. Thus there is a relatively great uniformity at

the Specific Cost (€/MWxMWh/yr) of the power plants.

The Author

Panagiotis Bourbourakis graduated in the Department of Mechanical & Aeronautical Engineering of the Technological

University of Patras and attended post-graduate courses in Energy and Environment (NTUA). He is currently working for theHydroelectric Power Department of PPC Renewables SA, as head of Operation & Maintenance, and as Technical Advisor for the

construction, erection and commissioning of hydro power plants.

Documents

HYDRO 2013 Full Paper