Solar Heater

Machine Learning for Solar Water Heater

Machine Learning (ML) for Solar Water Heater Supply and Demand

ML model is prepared to predict the supply and demand of hot water for the small and micro-scale industries in India. The ML models is trained with various seasonal and climate data. The prime aim of this model is to optimize energy use while keep maintaining supply and demand at their best.

> The model will be re-trained with the year 2023 weather data.

Project Collaboration

This project is jointly conducted by Prof. Kamlesh Parmar and Nirmal Parmar. Prof. Kamlesh Parmar is responsible for conducting the experiments on the solar water heater under different climate conditions or/and dynamic supply and demand of the hot water. Whereas Nirmal Parmar is mainly working on preparing data-driven solutions ( classic ML models and Artificial Neural Networks) for the demand and supply of solar water heaters.

M.Tech. Thesis

SWH for micro-small industries

Thesis: PREDICTION OF THERMAL PARAMETERS FOR FLAT PLATE SOLAR WATER HEATER BY MACHINE LEARNING

Student: Faizan Hafez

Supervisors: Prof. Kamlesh Parmar, Dr. Nirmal Parmar, PhD

Find more info in the link below.

GitHub - nirmalparmarphd/swh_ML: SWH for micro-small industriesSWH for micro-small industries. Contribute to nirmalparmarphd/swh_ML development by creating an account on GitHub.

Related Publications

Prediction of Thermal Parameters for Flat Plate Solar Water Heater by Machine Learning - A ReviewThe world has been in greater need of energy over the past few years; thus, researchers have been working consistently on the development of solar energy-based applications. Solar based applications are one of the best options because it is endlessly abundant and perfect for both industries and domestic applications. The present review is majorly focused on studying the possibilities of using solar water heaters and optimizing a heating process with advanced machine learning for micro or/and small-scale industries in India. Small-scale industries such as hospitals, chemical plants, and waste management plants continuously require hot water. They primarily rely on electric heaters or/and gas heaters. These heaters run directly or indirectly on fossil fuels and may cause harm to the environment. To avoid the consumption of fossil fuels and to use solar energy as a primary energy source of heating, introducing solar water heating integrated with machine learning is worth exploring. Various thermal parameters such as mass flow rate, irradiation, tilt angle, wind speed, and designing parameters have their effects on the performance of solar water heating systems. The present article review conducted on the study of thermal parameters, nanofluid as a working heat transfer fluid, and machine learning use in solar water heating applications which can enhance the system performance.

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