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Erschienen in:
2020 | OriginalPaper | Buchkapitel
40. Energy Demand Prediction Using Linear Regression
verfasst von : T. Manojpraphakar, Soundarrajan A
Erschienen in: Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications
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Abstract
Big Data analytics is the latest emerging technology that requires deep knowledge in business intelligence, machine learning, and statistical methods and in deep learning. It focuses on the application of data analytics for energy demand management using real-time data. The data is then analyzed for clustering, demand forecasting, pricing, and energy generation optimization. It represents a method to predict energy usage, based on real-time data obtained from TANGEDCO-CBE, using the linear regression model (LR). The final linear regression models developed were based on daily sustained demand and consumption by comparing actual and predicted energy usage models can predict with acceptable errors. Normally the energy requirement and industrial demands are high; hence the application of these energy Big Data analyses significantly improves efficiency and provides new business opportunities.