Variant Mode Data Analytics in Predicting the Radiation Effect on Solar Power Generation using Machine Learning Algorithms | IEEE Conference Publication | IEEE Xplore

Variant Mode Data Analytics in Predicting the Radiation Effect on Solar Power Generation using Machine Learning Algorithms

Publisher: IEEE

Abstract:

Power harvesting using solar power is the recent trend and innovations happening in deploying many types of equipment working with solar power. This is harmless and great...View more

Abstract:

Power harvesting using solar power is the recent trend and innovations happening in deploying many types of equipment working with solar power. This is harmless and greatly reduces pollution and is eco-friendly. The government also provides more concessions for establishing these solar power harvesting methods. There are two subsystems in solar power generation like sensor management systems. The subsystems have to be managed by predicting the power generation and identifying the right time for panel cleaning, and maintenance. In solar power generation systems, it is necessary to identify the faulty equipment and replace it for robust power generation. In the proposed article we are predicting the effect of ambient temperature, and module temperature on radiation of the solar power generation system using the Weka machine learning tool using algorithms like SMOreg, Linear regression, KNN, and Multilayer Perceptron. The prediction model predicts the solar power radiation with Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 0.0294 and 0.0558 of the Ambient and module temperature respectively. The prediction of radiation in the solar power plant will be helpful in grid maintenance, efficient use of accessories, identifying and servicing the sub-optimally performing unit to increase the daily yield, and reducing the operational cost.
Date of Conference: 29-30 July 2022
Date Added to IEEE Xplore: 14 October 2022
ISBN Information:
Publisher: IEEE
Conference Location: Hassan, India

I. Introduction

The advancement of human civilization has resulted in fast industrialization, which has been accompanied by urbanization and globalization, resulting in increased global energy demand. Conventional energy sources, which face rapid depletion, appear to be unable to meet soaring energy demand on their own. Solar, as a ubiquitous and environmentally beneficial source of renewable energy, has become one of the most widely used power production technologies in a variety of applications. To get the most out of a solar photovoltaic (SPV) system, it needs on be set to maximum power generation. The existence of life with sustainable energy is almost very difficult and the harvest of energy with an alternative source is very important in the context of developing countries, the conventional method is predicted to be extinct concerning time and globalization. The socioeconomic of a country greatly depends on the consumption of energy and also directly impacts the economic growth of a country. Energy harvested has different forms la like thermal power plants, nuclear power plants, windmills, and so on. One of the trending methodologies of harvesting power is solar power plants. A country like India is best suited for establishing a solar power plant. Sun energy is available in abundance and can be transformed from solar energy to electrical energy. Since energy can neither be created nor destroyed. Methane, biogas is one of the most commonly used power from fossil fuels to generate energy which is very costly for establishing, comprehensive, unreplenishable, and decreases day by day. As a part of sustainable resources, India has stepped into solar power harvesting which is one of the renewable energy resources replacing fossil fuels and other types of power generation to meet the thirst for energy. This solar photovoltaic method of energy is relatively very cost-effective, and eco-friendly compared to other chemical or oil-based electricity generation. Hence in our near future, Solar power plant is believed to be the most effective, efficient, and sustainable type of energy generation and null effect on environmental degradation. Solar electricity, in general, is becoming more economical every year. Solar panels have cheap operational expenses compared to other power generation technologies since they can create a huge amount of electricity compared to other power generation technologies since they can create a huge amount of electricity without compared to other power generation technologies since they can create a huge amount of electricity without the use of fuel. Another benefit of solar energy is that it is scalable, meaning it can be used to power a single residence or an entire factory. Overall, the sun emits undeniably more energy than we require; yet, the ability to convert it to electrical energy cost-effectively and in a cost-effective manner and to store electricity for nighttime and rainy days is a limitation. Solar power is a CO2-free, renewable energy source that has a substantially lower environmental impact than other power generation technologies. The key elements that affect the environment are the unique materials necessary for solar panel production, location, and the water required for solar panel cleaning [3–4]. The efficient use of solar panels, inverters, and grids in large-scale solar plants will reduce the cost and space necessary to generate the required power, reducing the environmental impact. Machine Learning (ML) methods will be increasingly beneficial in evaluating and generating models from solar plant data to maximize hardware use.

References

References is not available for this document.