Lessons learnt in Saudi Arabia with Solar PV system performance under desert conditions

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1 Lessons learnt in Saudi Arabia with Solar PV system performance under desert conditions

2 Campus Solar Roof Top Solar Thermal Solar PV 2

3 Campus Solar Roof Top 2MWp PV 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 m 2 Saves 1,700 tonne of carbon emissions annually 3

4 KAUST - CMOR Solar Roof Top 320KW PV 320 KW Power Generation facility 1, Wp modules over 1,950 m 2 4

5 KAUST - Campus Solar Roof Top 2MW PV 5

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9 Megawatt Hours Megawatt Hours Campus PV Energy Generation Building 3 PV Energy Generation ( MWh) Building 4 PV Energy Generation ( MWh) Campus PV Energy Generation Building MWH CMOR MWH Building 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

10 Onsite Renewable Energy (MWh) - Campus 2013 Onsite Renewable Energy (MWh) - Campus 2013 Onsite Renewable Energy - Campus 2013 Onsite Renewable Energy - Campus 2014 Onsite Renewable Energy - Campus January Febuary March April May June July August September October November December

11 PV Plant O&M in Desert Areas

12 Steps for Devising and O&M Plan 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

13 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

14 What defines a successful O&M plan Key Performance Indicators (KPI s) Performance Ratio (PR) Plant Availability Actual Generation vs. Predicted Energy losses Unscheduled Outages

15 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

16 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

17 O&M Case study (2 MWp and 5 MWp) Item 2 MWp case 5 MWp Total Weekly system cleaning 15 hours (11,500 m 2 ) ~45 hours (28,750 m 2 ) Daily cleaning hours 3 hours 8 hours Detergent usage - glass cleaner ( biweekly) Water flow rate ( ~ 1 m 3 /hr at SR 6 /m 3 ) Wages Worker Wage:SR3,000/month Technician wage: SR4,000/month 5L/month SR100/month SR350/Month SR16,000/month 4 workers/day 1 Technician ~8 L/month SR250/Month SR900/Month 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 $US/KWp/year Cost per unit area 4.73 $US/m 2 /year 1.97 $US/m 2 /year Cost Per clean $US/m 2 /clean $US/m 2 /clean

18 Other O&M related costs 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

19 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

20 O&M Cost ($/KW/Year) O&M Costs for different Technologies O&M Cost ($/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$ O&M costs for different system types Insurance, Property Taxes, Owner's Costs Inverter replacement Reserve Unscheduled Maintenance Scheduled Maintenance/Cleaning 0 Fixed Tiled C-Si Fixed Tilt CdTe Fixed-Tilt a-si Tilted Single-Axis Tracking c-si System Type Source: Addressing Solar PV O&M Challenges, NREL Singled-Axis Tracking C-Si

21 PV Plant Monitoring

22 Field Performance Indicators Efficiency = Energy out / Energy in Device Area The solar resources Maximum Power point P max Performance Ratio (Actual vs. Simulated) Specific Yield (Energy Generated/ P max ) Measurement Challenges!!

23 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

24 Another way to monitor soiling

25 Performance degradation due to Soiling

26 How big is the dust problem? 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 26

27 Cleaning Scheduling 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 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

28 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

29 LCOE ($cent/kwh) Plant O&M Cost Optimization 35 Effect of Cleaning Frequency on LCOE $1 2$ 3$ Cleaning Cycle (Days) 5MWp System

30 LCOE ($cent/kwh) LCOE ($cent/kwh) PV Plant LCOE Analysis Effect of Cleaning Cost on Plant LCOE vs. cleaning cost for different Capex Effect of PV efficiency on Dust Impact to LCOE $ 15 1$ 2$ 2$ 10 3$ 10 3$ Cost of Cleaning ($/m 2 /year) 5 MWp system, Cleaning every 6 days System Efficiency 5 MWp system, cleaned every 6 days % increase in O&M cost %Increase in LCOE % Increase in Efficiency % Reduction o

31 What about Dust Storms? 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

32 Potential surface impurities 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.

33 PV plant Cleaning Methods KAUST King Abdullah University of Science and Technology 33

34 Cleaning device (Robotic) 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 KAUST King Abdullah University of Science and Technology 34

35 O&M Plan goes wrong! 35

36 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

37 THANK YOU! Tamer Shahin Project Engineer Economic and Technology Development - KAUST King Abdullah University of Science and Technology 37

38 References 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