12.-Tamer-Shahin-KAUST.pdf

Lessons learnt in Saudi Arabia with Solar

PV system performance under desert

conditions

Campus Solar Roof Top

2

Solar PV

Solar Thermal

Campus Solar Roof Top 2MWp PV

3

• Mono Crystalline Silicon cells (Efficiency ~18.4 %)

• Simulated annual generation of 3,281 MWh

• First large scale grid-connected, roof top, solar power plant in Saudi Arabia

• Special Operating conditions

• Mono-crystalline performance in High Temperature environment

• 9,300 modules 215 Wp modules over 11,600 m2

• Saves 1,700 tonne of carbon emissions annually

KAUST - CMOR Solar Roof Top 320KW PV

4

• 320 KW Power Generation facility

• 1,072 300 Wp modules over

1,950 m2

KAUST - Campus Solar Roof Top 2MW PV

5

2012 Campus PV

Energy

Generation

566.9

MWH

567.5

MWH

Building 4

Building

3

65 MWH

CMOR 1020

92.8 101.2

130.8 145.8

148.1

180.9 169.6

156.4 142.1 136.7

117.0 111.6

0

20

40

60

80

100

120

140

160

180

200

Me

ga

wa

tt H

ou

rs

2013 Building 4 PV Energy Generation (1633.0 MWh)

92.3 101.7

129.9 144.0

145.1

180.7 170.0

156.6 140.0 137.7

116.5 112.0

0

20

40

60

80

100

120

140

160

180

200

Me

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2013 Building 3 PV Energy Generation (1626.3 MWh)

4,393.8 Megawatt Hours of

supplemental energy has been

added to the Campus Electrical

power grid with the

implementation of the Campus

PV Energy Generation Program

in 2012

A purchased energy cost

avoidance of $175,760 over 17

months, assuming 15 Halala per

KWh

Campus PV Energy Generation

124

147

261

290 293

362

340

313

282 274

235

259

244 244

100

150

200

250

300

350

400

January Febuary March April May June July August September October November December

Onsite Renewable Energy (MWh) - Campus 2013

Onsite Renewable Energy - Campus 2013 Onsite Renewable Energy - Campus 2014 Onsite Renewable Energy - Campus 2015

Onsite Renewable Energy (MWh) - Campus 2013

PV Plant O&M in Desert Areas

• Analyze site location (Need for cleaning)

• (Starts before system design)

• Soiling rate and content

• Wind, Temperature, Irradiation, Humidity

• Nearby pollution (traffic, construction, industry, agricultural

activities)

• System Characteristics

• (e.g. roof vs. ground, size, technology, configuration, tilt,

height, trackers, surface material)

• Number of arrays, meters, inverters

• Evaluation of available technical support from suppliers

Steps for Devising and O&M Plan

• Logistical challenges

• Analyze cost of energy, contractual obligations

• Warranty terms and conditions

• Desired level of monitoring

• Analyze cleaning frequency, cleaning method and

cost of cleaning

• Resources allocation and budgeting

• Define Key Performance Indicators (KPI’s)

• Implement Monitoring

• Contingency plans

Steps for Devising and O&M Plan

• Key Performance Indicators (KPI’s)

• Performance Ratio (PR)

• Plant Availability

• Actual Generation vs. Predicted

• Energy losses

• Unscheduled Outages

What defines a successful O&M plan

Optimized Cleaning Frequency and

Procedure (Manual)

• Finding the optimal cleaning

frequency and method

• Finding the optimal cleaning

procedure

• Reduce the O&M costs of running

the system and the overall LCOE

for a faster ROI

KAUST King Abdullah

University of Science and

Technology 15

O&M Study Case – KAUST 2MWp system

• The operating team consists of one technician/supervisor and 4

workers

• Cleaned once every 6 days

• Cleaning Procedure:

• The roof top is divided into 6 sections

• Each day one section is cleaned,

• Cleaning is done by a water hose, first cleaning round with soap

(first 6 days), and the next with water only

16

Item 2 MWp case 5 MWp

Total Weekly system cleaning 15 hours (11,500 m2) ~45 hours (28,750 m2)

Daily cleaning hours 3 hours 8 hours

Detergent usage - glass cleaner

( biweekly)

5L/month

SR100/month

~8 L/month

SR250/Month

Water flow rate

( ~ 1 m3/hr at SR 6 /m3)

SR350/Month SR900/Month

Wages

Worker Wage:SR3,000/month

Technician wage: SR4,000/month

SR16,000/month

4 workers/day

1 Technician

SR16,000/month

Same!

Other cleaning related costs >SR550/month >SR600/Month

Total monthly cost to clean ~SR17,000/month ~SR17,750/month

Yearly cleaning cost 54,400 $US 56,800 $US

Fixed O&M Cost 27.2 $US/KWp/year 11.36 $US/KWp/year

Cost per unit area 4.73 $US/m2/year 1.97 $US/m2/year

Cost Per clean 0.079 $US/m2/clean 0.033 $US/m2/clean

O&M Case study (2 MWp and 5 MWp)

• Cleaning brushes and other consumables (SR500/year)

• Pyranometers and instruments calibration (??)

• Replacement of damaged parts (??)

• Monitoring and data connectivity (SR300/Month)

• Other O&M activities:

• Electrical testing

• Monitoring, networking and data administration

• Ground maintenance

• Rack, foundations, and solar equipment inspections

Other O&M related costs

PV O&M

Preventative Maintenance:

- Panel Cleaning

- Ground Management

- Wildlife prevention

- Water Drainage

- Retro-commissioning

- Data collection and

monitoring maintenance

- Power conversion system

maintenance

- Annual inspection may

suffice for warrantee and

insurance compliance

Corrective Maintenance:

- On-site monitoring

- Incident/performance driven

(critical and non-critical)

- Warranty enforcement

Predictive Maintenance

- Spare parts

- Planned equipment

replacement

- Weather forecasting

O&M Costs for different Technologies

O&M Cost ($/KW/Year) Fixed Tiled C-Si Fixed Tilt CdTe Fixed-Tilt a-Si Tilted Single-Axis Tracking c-Si Singled-Axis Tracking C-Si

Scheduled Maintenance/Cleaning 20$ 25$ 25$ 30$ 30$

Unscheduled Maintenance 2$ 2$ 2$ 5$ 5$

Inverter replacement Reserve 10$ 10$ 10$ 10$ 10$

Subtotal O&M 32$ 37$ 37$ 45$ 45$

Insurance, Property Taxes, Owner's Costs 15$ 15$ 15$ 15$ 15$

Total O&M 47$ 52$ 52$ 60$ 60$

0

10

20

30

40

50

60

70

Fixed Tiled C-Si Fixed Tilt CdTe Fixed-Tilt a-Si Tilted Single-AxisTracking c-Si

Singled-AxisTracking C-Si

O&

M C

ost

($/K

W/Y

ear)

System Type

O&M costs for different system types

Insurance, Property Taxes, Owner's Costs

Inverter replacement Reserve

Unscheduled Maintenance

Scheduled Maintenance/Cleaning

Source: Addressing Solar PV O&M Challenges, NREL

PV Plant Monitoring

Field Performance Indicators

• Efficiency = Energy out / Energy in

• Device

• Area

• The solar resources

• Maximum Power point Pmax

• Performance Ratio (Actual vs. Simulated)

• Specific Yield (Energy Generated/ P max)

Measurement Challenges!!

Plant Monitoring

• Important for high performance

• Immediate detection of plant issues

• Affected by:

• The atmosphere

• Geographical location

• Altitude

• Sources of errors:

• Total Irradiance

• Spectral Irradiance

• Spatial Uniformity

• Temporal Instability

Monitoring is instrumental!

Need Continuous Measurements over extended periods of time before construction

Another way to monitor soiling

Performance degradation due to Soiling

How big is the dust problem?

26

• Technology specific

• Location specific

• 10-15% efficiency loss in one month of no

cleaning

• 5-7.5% unavoidable energy loss of power

plant

• The decrease in solar energy efficiency due

to dust storms was measured to be 60%.

• Dust effect on performance varies per

location and per technology

• Needed models for recommended frequency

of cleaning

• Incident Driven:

• Immediately after dust episodes (dust

storms, dusty weather, light rain)

• Regular Cleaning

• Frequency: Every 1-3 weeks (depending

on the case)

• No necessarily uniform across the

power plant

Cleaning Scheduling

• Cleaning Frequency calculation

• Site Specific

• Technology Specific

• Plant Specific (Tilt angle, orientation)

• Non-uniformity across the plant

• Seasonal change

• Based on cost of cleaning

• Cost of Energy

• Accepted tolerance to loss

Effect of efficiency on Cleaning cost

• Dust accumulation is a surface property

• For the same peak power lower efficiency modules will require

more cleaning

• Efficiency affects on LCOE:

• Higher efficiency lower BOS cost (Not the scope of this study)

• Higher efficiency lower O&M cost

Plant O&M Cost Optimization

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0 5 10 15 20 25 30 35

LC

OE

($cen

t/K

wh

)

Cleaning Cycle (Days) 5MWp System

Effect of Cleaning Frequency on LCOE

$1

2$

3$

PV Plant LCOE Analysis

30

0

5

10

15

20

25

30

0 1 2 3 4

LC

OE

($cen

t/K

wh

)

Cost of Cleaning ($/m2/year) 5 MWp system, Cleaning every 6 days

Effect of Cleaning Cost on Plant LCOE vs. cleaning cost for

different Capex

1$

2$

3$

% increase in O&M cost %Increase in LCOE

62.5 9.712838

0

5

10

15

20

25

30

8 13 18 23

LC

OE

($cen

t/K

wh

)

System Efficiency 5 MWp system, cleaned every 6 days

Effect of PV efficiency on Dust Impact to LCOE

1$

2$

3$

% Increase in Efficiency % Reduction o

50 7.69965

• 60% losses were recorded after a sand storm incident

• Translates to a 30% energy production loss for a week

• Results in 21 MWh loss (e.g.. in case of October for the 2MWp system)

• Frequency of dust storms needs to be predicted and considered

in the financial model

• Plant must be cleaned directly after dust storm incident

What about Dust Storms?

• Dust Particles natural

• Dust particles due to human activities (traffic, agricultural and

construction activities)

• Salt Particulates

• Pollen from Plants and traffic

• Dirt from birds

• Main Ingredients of Dust:

• Oxide metals: SiO2, Al2O3, FeO, CaO

• Carbonates: CaCO3, MgCO3

• Heavy metals: Lead, Iron, Arsenic, Manganese, Vanadium,

Nickel, Chromium, etc.

Potential surface impurities

PV plant Cleaning Methods

KAUST King Abdullah University of Science and Technology 33

Cleaning device (Robotic)

KAUST King Abdullah University of Science and Technology 34

• Emerging Dry-type cleaning/dusting robot for PV panels

• Using minimal amounts of water for cleaning PV panels

• Aimed for high reliability long life operation

• with minimal maintenance

• Reduces the O&M costs

O&M Plan goes wrong!

35

Safety and Personnel Protective

Equipment (PPE)

• Specialized killed labor is needed

• Proper training should be provided

• Workers should use all appropriate PPE:

• Gloves

• Sun caps/Helmets

• Sunglasses

• Face covers for blocking the sun

• Anti-slip shoes

• Safety Harness for working at heights

King Abdullah University of Science and Technology 36

King Abdullah University of Science and Technology 37

THANK YOU!

Tamer Shahin

Project Engineer

Economic and Technology Development - KAUST

References

• http://nextphasesolar.com/wp-content/uploads/2011/12/NREL-epri-OM-best-practices.pdf

• http://alectris.com/implementing-a-successful-om-strategy-for-solar-pv-2/

• http://nextphasesolar.com/wp-content/uploads/2011/12/NREL-epri-OM-best-practices.pdf

• http://www.nrel.gov/analysis/tech_lcoe.html

• Impact of dust on solar photovoltaic (PV) Performance: Research Status, Challenges and

recommendations, Monto Mani, Rohti Pillai

• On-site PV characterization and the effect of soiling on their performance, Soteris A. Kalogirou, Rafaela

Agathokleous, Gregoris Panayiotou

• Best Practices for Mitigating Soiling Risk on PV Power Plants, A. AlDowsari, R. Bkayrat, H. AlZain, T.

Shahin

• Effect of soiling on Photovoltaic modules, Reinhart Appels, Buvaneshwari Lefevre

• Impact of cleaning using water and surfactants on the performance of Photovoltaic Panels, K.A.

Moharram, M.S. Abd-Elhady, H.A. Kandil, H. El-Sherif

• Review of Self-cleaning method for solar cell array, Gaofa He, Chuande Zhou, Zelun Li

• Addressing Solar PV O&M Challenges, NREL

• RISKS AND OPPORTUNITIES IN THE OPERATION OF LARGE SOLAR PLANTS, Solar POWER-

GEN 2013

King Abdullah University of Science and Technology 38