Scientists develop mathematical model for making accurate solar power generation forecasts, which will ease the adoption of solar energy
Scientists from Shoolini University, India, in collaboration with the National Institute of Technology, Hamirpur, India, have developed a new mathematical model to predict the output power of solar cells. By taking into account the degradation of the photovoltaic modules over time (as well as other external factors), this model is more accurate than existing ones. It will help produce precise power generation forecasts, facilitating the implementation of solar power systems and easing the transition towards renewable energy sources.
The world is in dire need of a large-scale transition away from fossil fuels and towards sustainable energy sources to prevent an environmental crisis. Thanks to recent advances in various scientific and engineering disciplines, solar cells have become a rising star in the field of renewable energy, reaching operational costs and performance close to those of the conventional electric grid.
However, in spite of the remarkable strides made in photovoltaics (PV) technology, the performance of the solar cell itself is only one part of the equation. For solar power projects to be funded and rolled out, decision-makers need to know ahead of time how much energy the installed PV systems will provide, both for technical and administrative reasons. Of course, since solar cells are devices that harvest solar radiation, their solar-to-electricity conversion performance is tied to a variety of external factors, such as cloudiness, temperature, and humidity. So, forecasting how much power a PV system will output over a given amount of time is not a straightforward task.
But in a recent study published in Solar Energy, a team of researchers led by Professor Shyam Singh Chandel from the Centre of Excellence in Energy Science and Technology at Shoolini University, India, in collaboration with the Centre for Energy and Environmental Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh, India, developed an innovative model for predicting the output of solar cells, which is much more accurate than existing models, and can help policymakers make that next giant leap in solar power installations!
Their approach is based on the well-established single-diode model, which offers sufficient accuracy without requiring too much computational complexity. The developed model can take into account three, four, or five different solar cell parameters depending on the level of precision needed. Most importantly, it considers the degradation of the solar cell components over time—something which previous models did not factor in.
To test the accuracy of their model under real conditions, the researchers first determined the values of the model parameters in a controlled experimental setup using a Class-A Sun Simulator over a test PV module. Once the parameters were determined and the predictions made, they studied a solar PV module and then 1 kWp PV system installed on the rooftop of the Centre for Energy and Environmental Engineering at the National Institute of Technology, Hamirpur. From there, the researchers gathered data to validate the predictions of their model.
The results are promising, as the predictions of the proposed model are more accurate than those of previous ones. Additionally, the researchers noted the number of solar parameters to include in the model so as to produce the best predictions with varied temperature and solar radiation intensities (in other words, with the time of day, season, and weather conditions). These insights will be helpful in future studies on solar energy, as Prof. Chandel explains: “Our model could be useful for developing PV power forecasting software capable of predicting daily, monthly, and yearly solar power generation, which is a crucial parameter for calculating the electricity supply and demand distribution, as well as for marketing PV systems.”
According to the researchers, their work could ultimately help improve the efficiency of solar cells and PV technology in large solar power plants, which are being installed both worldwide and locally under India’s National Solar Mission. “Being able to predict the output power of different PV technologies will help interested parties decide for the best option available in the market for a particular location,” explains Prof. Chandel, “Based on the foreseen energy generation and the selected technology, one can estimate the total expenditure and payback period for a given project.”
In short, this study will hopefully pave the way to a faster transition into renewable energy sources. Let us all keep pushing onwards towards our common goal of sustainability!
|Authors||Prashant Malik, Rahul Chandel, and Shyam Singh Chandel|
|Title of original paper||A power prediction model and its validation for a roof top photovoltaic power plant considering module degradation|
|Affiliations||Centre for Energy and Environmental Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh, India|
Photovoltaics Research Group, Centre of Excellence in Energy Science and Technology, Shoolini University, Solan
Reference information for EA:
|Latest article publication date:||Solar Energy, Volume 224, August 2021|
|Method of Research:||Computational simulation/modeling|
|Subject of Research:||Not Applicable|
|Conflict of Interest (COI):||The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.|
About Professor Shyam Singh Chandel
Shyam Singh Chandel is the founder Head of the Centre for Energy & Environmental Engineering at the National Institute of Technology in Hamirpur, Himachal Pradesh, India. He is currently working as Director of the Centre of Excellence in Energy Science & Technology at Shoolini University, also in Himachal Pradesh, India. He has over 40 years of experience in renewable energy, solar photovoltaics, passive solar housing technology, wind energy, and solar–wind-based hybrid systems. He is recognized as among the top 2% of energy researchers worldwide as per Stanford University World Ranking of Scientists and has published over 55 peer-reviewed papers.