Unveiling Hidden Insights: Role of Data Analytics for Stakeholders in Modern Energy Internet

The Energy Internet has ushered in a new era of energy management with diverse energy sources, shifting client needs and environmental concerns. Data analytics helps everyone solve challenges and seize opportunities in today's unpredictable environment. This essay explores the complex world of data analytics and its importance for Energy Internet workers. This essay emphasizes the importance of data analytics for energy professionals. It combines Time Series Forecasting, Machine Learning for Anomaly Detection, and Predictive Analytics for Renewable Energy Integration to create a novel method. These algorithms form a data-driven system to tackle the energy industry's biggest difficulties. A comparative study was done to fully review the procedure. This research compares the recommended strategy to corporate standards and highlights its merits and downsides. The effectiveness of these approaches is measured by MAE, RMSE, F1-Score, Precision, and Recall. The analysis found that the recommended technique strikes a good compromise between accurate forecasts and outliers. It consistently improves energy demand prediction, system stability, and green energy utilization. This comprehensive approach empowers everyone to make data-driven decisions, ensuring the long-term viability and efficiency of the contemporary Energy Internet.