Solar Simulator Pricing Guide
Have you ever wondered what goes into the cost of a solar simulator? From light source type to lab integration and long-term operational expenses, pricing is more than just the sticker on the box.
This comprehensive guide explores everything from initial purchase decisions to total cost of ownership (TCO), including a detailed comparison between xenon arc lamps and modern LED systems.
Whether you’re outfitting a new research lab or just exploring your options, this guide breaks it all down into clear, focused chapters. Each section delves deeply into key pricing factors to help you make confident and informed decisions.
Grab a coffee and explore our multi-part series on solar simulator pricing. You’ll also find references to our in-depth video content on LEDs, multi-source lighting, and best practices for lab testing.
What Drives Solar Simulator Pricing?
From build quality to spectral fidelity, various elements influence price. But the real question is: What are you paying for, and why does it matter?
Pricing decisions affect not only your budget, but also your lab’s ability to get reliable, repeatable results. Understanding what’s behind the price tag is the first step to choosing the right system.
That’s why we created this guide: to provide you with the tools and context you need to evaluate costs through a scientific and operational lens.
Solar Simulator Pricing Guide Table of Contents
If you are starting your journey into pricing a solar simulator, we suggest beginning with Chapter One. For those who have previously purchased solar simulators, feel free to explore the various topics covered in the chapters.
 Chapter 1: What Is a Solar Simulator? Understanding Artificial Sunlight for Lab Testing Solar simulators act as controlled “mini suns,” allowing researchers to replicate the sun’s light spectrum in a lab. This chapter introduces solar simulators, explains why they’re essential, and demonstrates how matching standardized spectra, such as AM1.5G and AM0, ensures experiments are reliable, repeatable, and independent of weather or location. |
 Chapter 2: Key Metrics and Standards What standard do you require? In this chapter, we examine the industry standards of IEC 60904-9 and ASTM E927, which define the performance of solar simulators. You’ll learn how spectral match, spatial non-uniformity, and temporal stability affect accuracy, along with newer metrics such as spectral coverage and deviation, which better reflect real-world testing needs. |
 Chapter 3: Solar Simulator Lamp Technologies Not all simulators shine the same. This chapter compares the two dominant lamp technologies: incandescent (xenon arc or metal halide) and LED. We cover trade-offs in spectral control, heat output, startup times, and lifetime, giving you the insights needed to choose the right light source for your application. |
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Chapter 4: A Solar Simulators Total Cost of Ownership (TCO) The sticker price is just the beginning. In this chapter, we break down the full cost of owning a solar simulator, including bulb replacements, maintenance, HVAC impacts, and the time savings from ease of use or automation. Learn how to assess both upfront and hidden costs when evaluating equipment quotes.
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 Chapter 5: Small Area Solar Simulator Return on Investment (ROI) Go beyond costs and discover the financial impact of your purchase. In this chapter, we guide you through ROI, IRR, and payback calculations for small area solar simulators, showing how data-driven comparisons of LED and xenon systems reveal dramatic long-term savings and fast returns, essential insights for choosing the right solar simulator for your work. |
Chapter 6: Large Area Solar Simulator Return on Investment (ROI) Explore the financial impact of investing in large area solar simulators. This chapter guides you through ROI, IRR, and payback calculations specifically designed for large-area testing, demonstrating how meticulous comparisons between LED and xenon systems can reveal substantial long-term savings and rapid returns. Gain essential insights for selecting the best solar simulator to maximize your research. |
References
Aghassi, A., and Fay, C. (2019). Effects of IPA treatment on the photovoltaic performance of bulk heterojunction organic solar cells. Journal of Physics and Chemistry of Solids, 130, 136-143.
ASTM E490-00a. (2019). “Standard Solar Constant and Zero Air Mass Solar Spectral Irradiance Tables”, ASTM International, West Conshohocken, PA, www.astm.org
ASTM E927-19 (2019), “Standard Classification for Solar Simulators for Electrical Performance Testing of Photovoltaic Devices”, ASTM International, West Conshohocken, PA, www.astm.org
ASTM E1021-15 (2019), “Standard Test Method for Spectral Responsivity Measurements of Photovoltaic Devices,” ASTM International, West Conshohocken, PA, www.astm.org
ASTM G173-03. (2020). “Standard Tables for Reference Solar Spectral Irradiances: Direct Normal and Hemispherical on 37° Tilted Surface”, ASTM International, West Conshohocken, PA, 2020, www.astm.org
Bliss et al. (2008). “Advantages in using LEDs as the main light source in solar simulators for measuring PV device characteristics”, Solar Energy and Applications, San Diego, CA. http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.795428
Emery, K.A. (1986). Solar Simulators and I-V Measurement Methods / Device Performance, Solar Cells, 18, 3-4. Retrieved online on 2021-06-25 from https://www.nrel.gov/docs/legosti/old/8666.pdf
European Commission Joint Research Centre. (2010). Guidelines for PV Power Measurement in Industry. Compiled Report.Retrieved online on 2021-06-25 from https://op.europa.eu/s/rX8a
Fernando, J. (2021). Internal Rate of Return Definition & Formula. Investopedia. Retrieved online on Sep 20, 2021 from https://www.investopedia.com/terms/i/irr.asp.
IEC. (2020). 60904-9: Classification of solar simulator characteristics.
Kagan, J. (2021). Payback Period Definition. Investopedia. Retrieved online on Sep 20, 2021 from https://www.investopedia.com/terms/p/paybackperiod.asp.
Leary, G. et al. (2016). “Comparison of xenon lamp-based and led-based solar simulators”, IEEE 43rd Photovoltaic Specialists Conference (PVSC), Portland, OR. http://ieeexplore.ieee.org/document/7750227/
Reese, M.O., Marshall, A.R., and Rumbles, G. (2017). Chapter 1: Reliably Measuring the Performance of Emerging Photovoltaic Solar Cells, in Nanostructured Materials for Type III Photovoltaics, 1-32. Retrieved online on 2021-06-25 from https://pubs.rsc.org/en/content/chapterhtml/2017/bk9781782624585-00001?isbn=978-1-78262-458-5
Sammis, T., O’Neill, M., and Wang, J. (2013). Research Report 781: Estimating Economic Value of Applied Research Projects. NM State University, Agricultural Experiment Station. Retrieved online on 2021-06-25 from https://aces.nmsu.edu/pubs/research/economics/RR781.pdf
Ye, S. et al. (2020). Resolving Spectral Mismatch Errors for Perovskite Solar Cells in Commercial Class AAA Solar Simulators, J. Phys Chem. Lett. 11, 10, 3782-3788. Retrieved online on 2021-06-25 from https://pubs.acs.org/doi/10.1021/acs.jpclett.0c00355#