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Table of Contents
Chapter 1: Introduction for Smart Grid Forecast and Dispatch
Chapter 2: Review for Smart Grid Forecast
Chapter 3: Review for Smart Grid Dispatch
Chapter 4: Deep Learning Based Densely Connected Network for Load Forecast
Chapter 5: Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecast of Electric Vehicles
Chapter 6: Dense Skip Attention based Deep Learning for Day-Ahead Electricity Price Forecast with a Drop-Connected Structure
Chapter 7: Dirichlet Process Mixture Model Based on Relevant Data for Uncertainty Characterization of Net Load
Chapter 8: Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power
Chapter 9: Data-driven Bayesian Assisted Optimization Algorithm for Dispatch of Highly Renewable Energy Power Systems
Chapter 10: Multi-objective Optimization Approach for Coordinated Scheduling of Electric Vehicles-Wind Integrated Power Systems
Chapter 11: Deep Reinforcement Learning Assisted Optimization Algorithm for Many-Objective Distribution Network Reconfiguration
Chapter 12: Federated Multi-Agent Deep Reinforcement Learning Approach via Physic-Informed Reward for Multi-Microgrid Energy Management
Chapter 13: Supply Function Game Based Energy Management Between Electric Vehicle Charging Stations and Electricity Distribution System.
Chapter 2: Review for Smart Grid Forecast
Chapter 3: Review for Smart Grid Dispatch
Chapter 4: Deep Learning Based Densely Connected Network for Load Forecast
Chapter 5: Reinforcement Learning Assisted Deep Learning for Probabilistic Charging Power Forecast of Electric Vehicles
Chapter 6: Dense Skip Attention based Deep Learning for Day-Ahead Electricity Price Forecast with a Drop-Connected Structure
Chapter 7: Dirichlet Process Mixture Model Based on Relevant Data for Uncertainty Characterization of Net Load
Chapter 8: Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power
Chapter 9: Data-driven Bayesian Assisted Optimization Algorithm for Dispatch of Highly Renewable Energy Power Systems
Chapter 10: Multi-objective Optimization Approach for Coordinated Scheduling of Electric Vehicles-Wind Integrated Power Systems
Chapter 11: Deep Reinforcement Learning Assisted Optimization Algorithm for Many-Objective Distribution Network Reconfiguration
Chapter 12: Federated Multi-Agent Deep Reinforcement Learning Approach via Physic-Informed Reward for Multi-Microgrid Energy Management
Chapter 13: Supply Function Game Based Energy Management Between Electric Vehicle Charging Stations and Electricity Distribution System.