Solar production with K means clustering

This presentation explores how K-means clustering can be used to analyze solar production data and identify patterns that can help optimize energy generation. visit https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/ for more

1. Solar Production with K-means Clustering - Tejas Bhogam

2. Introduction Solar-based energy is becoming one of the most promising sources for producing power for residential, commercial, and industrial applications. Energy production based on solar photovoltaic (PV) systems has gained much attention from researchers and practitioners recently due to its desirable characteristics. However, the main difficulty in solar energy production is the volatility intermittent of photovoltaic system power generation, which is mainly due to weather conditions. For large-scale solar farms, the power imbalance of the photovoltaic system may cause a significant loss in their economic profit.

3. Objective The objective of a solar power generation dataset is to provide comprehensive and structured data that can be used to analyze, model, and optimize the production of electricity from solar energy systems. This dataset typically includes various parameters and measurements that help in understanding the performance and efficiency of solar power installations. Forecasting and Prediction: Developing models to predict future power generation based on historical data, weather patterns, and other relevant factors. Optimization: Identifying ways to maximize power output and improve the overall efficiency of solar power systems. Comparative Studies: Comparing the performance of different solar technologies, configurations, or locations to identify best practices.

4. Dataset India is the world's third-largest producer and third-largest consumer of electricity. The national electric grid in India has an installed capacity of 370.106 GW as of 31 March 2020. Renewable power plants, which also include large hydroelectric plants, constitute 35.86% of India's total installed capacity This data has been gathered at two solar power plants in India over a 34-day period. It has two pairs of files - each pair has one power generation dataset and one sensor readings dataset. The power generation datasets are gathered at the inverter level - each inverter has multiple lines of solar panels attached to it. The sensor data is gathered at a plant level – a single array of sensors optimally placed at the plant.

5. Analysis

6. Checking the Data types

7. Checking null values There are no null values except one column i.e. previousYearToDate

8. Relationship between Month and Energy consume From the graph, we can say that energy consumption is high in the summer season.

9. Distribution of Year

10. Distribution of Value Column

11. Relationship between Value and YearToDate

12. Top 5 countries

13. Outliers

14. Label Encoding

15. K-means Clustering on Country