Smart Grid Analytics for Sustainability and Urbanization in Big Data

Overview & Synopsis

This reprint covers the following topics in the field of smart grids: 1. Optimal dg location and sizing to minimize losses and improve the voltage profile using garra rufa optimization. 2. Solar and wind energy forecasting for the green and intelligent migration of traditional energy sources. 3. Optimized micro-grid’s operation with electrical-vehicle-based hybridized sustainable algorithm. 4. The detection of nontechnical losses in smart meters using a MLP-GRU deep model and augmenting data via theft attacks. 5. A hybrid deep-learning-based model for the detection of electricity losses using big data in power systems. 6. Load frequency control and automatic voltage regulation in a multi-area interconnected power system using nature-inspired computation-based control methodology. 7. Line overload alleviations in wind energy integrated power systems using automatic generation control. 8. Electric price and load forecasting using a CNN-based ensembler in a smart grid. 9. Day-ahead energy forecasting in a smart grid considering the demand response and microgrids. 10. A dragonfly optimization algorithm for extracting the maximum power of grid-interfaced pv systems. 11. An economic load dispatch problem with multiple fuels and valve point effects using a hybrid genetic–artificial fish swarm algorithm. 12. Incentive-based dynamic pricing in a smart grid.