Blockchain-Based Smart Electricity Monitoring and Sustainable Grid System with Machine Learning-Powered Electricity Demand Forecasting

The increasing electricity demand and the utilization of renewable power sources bring to the forefront inefficiencies of conventional grids, such as inconsistent billing, transparency, and wastage of energy. This paper suggests the implementation of a blockchain-enabled smart electricity monitoring system integrated with machine learning-based demand forecasting. Blockchain provides safe, transparent transactions with no room for fraud and billing errors, while machine learning refines the distribution of energy through predicting the patterns of consumption based on LSTM and BiLSTM models. The envisioned system enables peer-to-peer energy exchange and real-time monitoring, cutting the cost of electricity and making the grid more efficient. Results from simulation illustrate enhanced accuracy of forecasting and security of transactions, showing the viability of a decentralized, green energy future.