Solar Energy & PV Modeling Expert (Physics-Based Calculations)
Budget: $25 – $50 USD
Description:
We are looking for an experienced solar energy specialist to support our development of a high-accuracy PV power prediction system. The ideal candidate has a strong physics background, deep understanding of solar irradiance modeling, and experience in PV system performance calculations using R or Python (PVLib, solaR, or similar tools). Ideally, you already worked in a PV forecast project.
Key Responsibilities:
Convert GHI, DNI, and DHI into POA irradiance using transposition models (Perez, Hay-Davies, Isotropic).
Implement PV power output calculations based on physics-based models (Sandia, CEC, NOCT).
Model inverter performance and system losses (shading, soiling, efficiency degradation).
Ensure high-accuracy deterministic modeling without reliance on machine learning.
Work with PVLib (Python) or solaR (R) for solar energy computations.
Requirements:
Degree (BSc, MSc, or PhD) in Solar Energy, Renewable Energy Engineering, Physics, or a related field.
Proven experience in solar energy modeling and PV system performance calculations.
Strong knowledge of solar irradiance transposition, module temperature effects, and inverter modeling.
Proficiency in Python (PVLib) or R (solaR) with demonstrated experience in similar projects.
Understanding of standard PV models (Sandia, CEC, NOCT) and industry best practices.
Project Scope:
Physics-based modeling only
Short-term contract with potential for extended collaboration.
Flexible hours, remote work.
IMPORTANT: You need to be able to explain us why and what you are doing. You will work together with ML Engineers. Please apply only if you are truly comfortable in the above topics.
If you feel you quality, we are happy to read your applicaton.
We are looking for an experienced solar energy specialist to support our development of a high-accuracy PV power prediction system. The ideal candidate has a strong physics background, deep understanding of solar irradiance modeling, and experience in PV system performance calculations using R or Python (PVLib, solaR, or similar tools). Ideally, you already worked in a PV forecast project.
Key Responsibilities:
Convert GHI, DNI, and DHI into POA irradiance using transposition models (Perez, Hay-Davies, Isotropic).
Implement PV power output calculations based on physics-based models (Sandia, CEC, NOCT).
Model inverter performance and system losses (shading, soiling, efficiency degradation).
Ensure high-accuracy deterministic modeling without reliance on machine learning.
Work with PVLib (Python) or solaR (R) for solar energy computations.
Requirements:
Degree (BSc, MSc, or PhD) in Solar Energy, Renewable Energy Engineering, Physics, or a related field.
Proven experience in solar energy modeling and PV system performance calculations.
Strong knowledge of solar irradiance transposition, module temperature effects, and inverter modeling.
Proficiency in Python (PVLib) or R (solaR) with demonstrated experience in similar projects.
Understanding of standard PV models (Sandia, CEC, NOCT) and industry best practices.
Project Scope:
Physics-based modeling only
Short-term contract with potential for extended collaboration.
Flexible hours, remote work.
IMPORTANT: You need to be able to explain us why and what you are doing. You will work together with ML Engineers. Please apply only if you are truly comfortable in the above topics.
If you feel you quality, we are happy to read your applicaton.