- Calibsun | Scientific publications
Scientific publications
CalibSun is a spin-off of Solais, a solar engineering consulting firm with over 15 years of expertise in the photovoltaic sector, which allows us to have an invaluable practical knowledge of PV financing, development and operations.
- Forecasting
- 2025
On the optimal selection of meteorological variables as inputs to machine learning models for solar irradiance forecasting
Variables output from numerical weather models are essential and widely used as inputs to machine learning models for forecasting the solar irradiance available at ground level. This abundance of data necessitates an effective optimization strategy to identify the most relevant features and eliminate those with limited impact in order to reduce computational resources.
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- BESS
- 2018
Strategies for the Combined Operation of PV/Storage Systems Integrated into Electricity Markets
This paper evaluates stochastic optimization and predictive models to safely integrate energy storage coupled with solar assets into commercial power grids, prioritizing system lifespan alongside revenue generation.
- BESS
- 2020
Combined Operation Strategies of PV – Storage Systems Integrated into Electricity Markets
Building on previous work, this paper details control strategies for PV/BESS installations in electricity markets. It introduces a Model Predictive Control (MPC) model that tracks battery degradation costs at both the day-ahead and real-time dispatch stages to prevent premature battery wear.
- BESS
- 2019
The Sizing of a PV/Battery System Through Stochastic Control and Aggregation of Installations
This research demonstrates how to decrease the required physical battery capacity (BESS) for market-integrated solar plants while keeping the same output quality. This is achieved using stochastic control algorithms and virtual portfolio aggregation.
- Probabilistic
- 2020
Towards a Simple and Robust Probabilistic Analysis of Solar Variability Based on the Probability of Transition Between Sky State Variability Classes
Solar variability is a key driver of grid instability in isolated or hybrid (PV/Diesel) power plants. This study models local solar variability by analyzing the mathematical transition probability between sky states, helping developers assess the feasibility and predictability of new hybrid installations.
- Probabilistic
- 2020
A Novel Approach for Seamless Probabilistic Photovoltaic Power Forecasting Covering Multiple Time Frames
This research adapts the Analog Ensemble (AnEn) model to generate continuous, transparent probabilistic forecasts across multiple time horizons. The algorithm can start at any point of the day and adaptively selects the most relevant inputs for each horizon, making it ideal for continuous intraday trading.
- Probabilistic
- 2021
A New Approach for Probabilistic Solar Forecasting Using Satellite-Based Cloud Motion Vectors
This paper introduces a method combining physical and statistical techniques. It uses clear-sky index data and Cloud Motion Vectors (CMV) from satellite feeds (traditionally used only for deterministic models) to generate precise probabilistic forecasts. Tested on ground-measured GHI data, the model reduces the Continuous Ranked Probability Score (CRPS) by 37% to 62% against standard baselines.
Scientific partners
Our authors
CalibSun was created in 2023 by Sébastien Pitaval and Nicolas Thévenin, the founders of Solaïs, a company that has been an expert in photovoltaics for more than 15 years and a leader in glare studies allowing .
- Calibsun’s resources
Our resources
Solar & data expertise
Deep-dive our specific know-hows on photovoltaic, solar resource and data science and how they enhance our services.
