Testing and evaluation program in NEO Overview of Current and Future - - PowerPoint PPT Presentation

New Energy Oasis (NEO)

Testing and evaluation program in NEO

Overview of Current and Future Projects

• Dr. Raed A. Bkayrat,

Manager Technology Application and Advancement Group (TAAG) Economic Development, KAUST

Technology Application and Advancement Group (TAAG)

2

TAAG

New Energy Oasis (NEO) Advance Science and Technology Training Pilot Projects + Prototyping Technical and Business consultation

Research-Driven Commercial Innovation

Research Basic Science Bench

Scale

Technology Maturity Developmental Pilot Technology Commercialization Commercial Production Industry

3

concept market

Technology Application and Advancement

Establishing the “Push and Pull” Factors

4

Saudi Industry International Technology Providers

Dust Mitigation Initiative

New Energy Oasis (NEO) Technology Application and Advancement Group (TAAG)

KAUST King Abdullah University of Science and Technology 6

Background Current Condition Goal Root Cause Analysis Proposed Solutionss Effect Confirmation Follow-up Actions

Current Condition

• The lack of government incentives has limited the widespread of large-scale solar farms
• Current wet cleaning methods are expensive & inefficient due to the scarcity of water in the region
• The optimum frequency of cleaning needs to be determined (e.g. $6,650/month - KAUST solar

panels)

• Remote areas requiring solar panel cleaning have limited access to water
• The drop of solar energy efficiency over three months without cleaning ranged between 30-45%
• Dust storms result in a 60% decrees in solar energy efficiency
• The Net Present Value of solar panels reduce by 1% annually due to panel degradation
• Leveled Cost Of Energy (LCOE) of solar in the Kingdom can’t compete with conventional electricity

rates (SR/kWh)

• High installation, running, O&M costs (MENA) prevent solar generation from reaching Grid Parity

Background

• Areas with large solar energy potential are the dustiest in the world with limited rainfall
• Domestic oil consumption is projected to consume 45% of total oil produced in the Kingdom by 2030
• At the current pace, domestic demand for power is expected to nearly triple by 2030
• Energy demand continues to increase at an alarming rate in the Kingdom (50 barrels of oil/person

annually) without a sustainable energy solution

Project Developer: Hashim Al-Zain Team Sponsor: Raed Bkayrat Updated: 24 March 2012 Version 0.2

Goals 1st to understand & quantify the impact of soling on the performance of solar systems. 2nd to develop a number of dust mitigation products & technologies and measure their efficacy through reproducible test procedures. 3rd to evaluate different mature dust mitigation technologies and solutions. This is to validate the ability of achieving 100% dry-type cleaning solutions & to recommend cleaning frequency based on field testing of technologies and site-specific cleaning method. Cause-Effect Diagram Proposed Solutions Preliminary Results

• The increase in system efficiency goes up to 30-45% increase when system is cleaned after

three months of no cleaning

• Dust deposits on solar panels show physical irregularities with chemical traces of salt,

metals, hydrocarbons, and biological content Moving Forward

• Assigned advisory committee: Tom Missimer, Kim Choon Ng, and Ghassan Jabbour, Moa’awia

AlMasri, Maen AlAmad

• Stakeholders: SABIC, glass & solar companies, solar project developers, utility companies,

technology developers

1. What is the level of maternity of each proposed technology? 2. What are the predicted results for each Proposed Solutions? What is the impact on glass surfaces? 3. Are the Proposed Solutions focused on the right areas? How easy are they to implement? 4. Is the implementation order clear? How will the effects of the Proposed Solutions be verified? 5. What is the impact on the bottom-line LCOE? What is the cost of the proposed solution? 6. Are the results reproducible? 1. How does the system actually behave with the Proposed Solutions that are being proposed for implementation in place? (passive vs. active) 2. How will you measure the effectiveness of the Proposed Solutions? 3. What have we learned that does or does not improve the situation? 4. In light of learning, what should be done? 5. How should the way we work or our standards be adjusted to reflect what we learned?

Reduced Solar Efficiency Infrastructure Utilities O&M Weather Connection to gird Mounting structure arrangement Proximity to service center No Proven reliable solution Access to Water Dust Composition Cost of cleaning Wind O&M subsidies Dust Mitigation R&D Endorsements High Temperature Lack of Rain High Humidity Dust deposition Clay presence Organic material presence Aerosol Dust Mitigation Dry Passive Coatings Sputtering Coating Super- Hydrophobic Ultrafine TiO2 PCO Active Cleaning EDS Clean Fizz Rotary Brush Wet

1. What do we need to learn next? 2. What remains to be accomplished? 3. What other parts of the organization need to be informed of this result? 4. How will this be standardized and communicated?

Coating Performance Solar Panel Efficiency Technology Maturity Environmental Durability Field Evaluation Economics Reliability O&M

Dust Mitigation Program

• How is Dust Mitigation Initiative executed?
• Providing solution for Dust effects on solar PV
• Evaluating of different technologies and solutions
• Field testing

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Temperature and Dust Effects Analysis

• Temperature
• Testing and verifying the effects of temperature on decay

coefficients

• Dust
• Testing and verification of performance against dust accumulation
• 1 month Test vs. round-the-year Test
• Other Factors

Dust Accumulation Test

• Standard sample collection and data analysis method
• Lab analysis of dust samples
• Spectral analysis and effects of dust on transmission of light
• Weight analysis (can be used as a measure of dust accumulation

versus time)

• Physical Analysis (Shape, count, and size of particles)
• Chemical Analysis: Metals, Salts, PH, Biological Contents,

Hydrocarbons, etc

• Standard report template to be delivered

Benefits of the Dust Analysis

• Recommendation of coating materials and surface design
• Asses the performance of different PV technologies against dust effects (in the

future also solar thermal may be included)

• Recommendation of cleaning frequency (for different coatings and different

technology)

• Recommendation of cleaning techniques and methods
• Better understanding and predict O&M, LCOE, and other factors effected by dust
• Reduce the cost by using optimized service costs (faster ROI)

Other Parts of the study

• The study will include
• Effect of Tilt on dust accumulation
• Finding the optimum Tilt to increase harvested light( by reduction of dust accumulated

versus the reduced solar energy normal to the surface)

• Effects of humidity (in collaboration with other testing locations)
• Effects of temperature (temperature analysis is another test done at NEO)
• Effects of other environmental factors, like nearby factories and pollution of the air

(done by comparing different test locations)

• Effect of dust on the performance of mirrors and other concentrating optics

Preliminary Results

New Energy Oasis- DUST MITIGATION INITIATIVE (DMI)

Sample Results

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System Performance Data

5 10 15 20 25 30 35 40 45 50 0.5 1 1.5 2 2.5 3 3.5 4 27-Jan 6-Feb 16-Feb 26-Feb 8-Mar 18-Mar 28-Mar 7-Apr 17-Apr 27-Apr 7-May Temperature (0C) Specific Yield (Kwh/Kwp) Time

Kwh/Kwp Performance

System 1 System 2 Temperature

Dust Accumulation effect on PV performance

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5 10 15 20 25 30 35 40 45 50 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% 50 100 150 200 250 Maximum daily temperature (oC) Efficiency (%) Day

Efficiency drop due to dust Accumulation

Efficiency String 2 Efficiency String 1 Max of Ambient Temp

30-45% increase!

Cleaning Program

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0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 2 4 6 8 10 12 14 16 18 20 String Efficiency (%) Day

Dust Effects on System Efficiency

String1 Eff String2 Eff String3 Eff String4 Eff String5 Eff

Sample Results

• Effect of Dust on Spectral Transmission of the glass
• Clarify the behavior of different technologies under

the effect of dust

• Study the behavior of a specific product under dust

accumulation

• Currently this is only for direct light. In the future,

further tests will also include the diffused, scattered, reflected and absorbed light

Spectral Analysis and effects on Transmission

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10 200 400 600 800 1000 1200 1400 1600 1800 2000 Relative Glass Transmission Wavelength (nm)

Effect of Dust on Glass Transmission

Week 1 Week 2 Week 3 Week 4

• Particle Size Distribution
• Information to be extracted:
• Most common Particle Size
• Total No of particles (particle/m2)
• Estimation of Area Blockage (%)

(Versus Time) Duration of exposure to dust: 60 days

Sample Results

• Particle Shapes
• Particle-to-surface interaction
• Detailed study on local dust characteristics
• Other physical characteristics

Physical Analysis of Dust Particles

Sample Results

• Particle Shapes
• Particle-to-surface interaction
• Detailed study on local dust characteristics
• Other physical characteristics

Physical Analysis of Dust Particles

Weekly Dust Accumulation

Sample Results

• Data that can be extracted:
• Dust content Chemical Distribution (Chemical Composition of

the dust)

• Availability of Salts
• Metal Contents of the dust
• Hydrocarbons content
• Biological Content of the dust (from existence of bacteria and
• ther information, Not easy to get, needs expert analysis)
• Existence of a specific element and its quantity

Chemical Analysis and Composition

Further Studies- Dust Analysis

• Effect of change of tilt
• Find the optimum tilt angle to install to minimize dust
• Effect on different coatings
• Effects of wind speed and direction
• Effect of dust on the Panels/Modules:
• The effect of module edge on dust collection
• Effect of height from the ground
• Effect of dust on Mirrors, concentrators and receivers

Weekly Dust Accumulation

Sample Results

• The Plots for the performance is being recalculated and not available for

the time being but the constitute the following plots

• Efficiency(%)= (AC Energy Output/ Solar Irradiation Energy Input)
• Specific Yield (Kwh/Kwp) = (Energy Output/Peak power rating of the

system)

System Performance Data

10% 11% 12% 13% 14% 15% 16% 17% 18% 20 25 30 35 40 45 50 55 60 65 70 Energy Conversion Efficiency Daily Maximum Module Temperature oC Eu = Generated Energy / Incident Irradiation Energy (%)

Module Temperature Effect

Linear Eu

TAAG - King Abdullah University of Science and Technology

Dust Accumulation on the surface

Dust accumulation on the surface of PV panels in New Energy Oasis (NEO)/KAUST

Dust Mitigation Program

• Dust Evaluation
• Chemical Composition Analysis
• Physical Properties Analysis
• Rate of Accumulation Analysis
• Spectral Behavior Analysis
• Dust Effect on Performance
• Performance Testing Protocol
• Performance of different technologies under Dust Accumulation
• Cleaning Frequency and LCOE optimization
• Cleaning Techniques
• Dust Mitigation Techniques
• Active Techniques
• Passive Techniques

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Dust Mitigation Techniques

• Passive Techniques
• Dust Mitigation Coatings (NTU, AUC,KAUST, Others)
• Evaluation of different Coatings
• Optimum Tilt Angle
• Active Techniques
• Electro-Dynamic Screen (EDS)
• Dry-Type Rotary Brush

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Results- Dust Control Program

• SulferCell
• Jump (around the day of cleaning)
• Decline (Efficiency vs time) (daily yield)
• ShowaShell performance testing
• efficiency of different sections vs time (or Kwh/Kwp)

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Optimized Cleaning Procedure

• Finding the optimal cleaning

frequency

• Finding the optimal cleaning

procedure

• Reduce the O&M costs of running

the system and the overall LCOE

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Solar Panel Cleaning Device (Dust repellant EDS Screen)

• Design of active coating material
• Same technology used on Mars rovers
• Working with international technology providers to develop a dust

repellant transparent screen

• Optimized for operation in Saudi Arabia

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Cleaning device (Robotic)

• 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

• Automated robotic device
• Reduces the O&M costs

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Raed Bkayrat, Technology Advancement Group raed.bkayrat@kaust.edu.sa