Smart Energy Management

Smart Energy Management

Data Driven Methods for Energy Service Innovation

Wen, Lulu; Zhou, Kaile

Springer Verlag, Singapore

02/2022

310

Dura

Inglês

9789811693595

15 a 20 dias

658

Descrição não disponível.
Chapter 1 Introduction.- Chapter 2 Residential Electricity Consumption Pattern Mining based on Fuzzy Clustering.- Chapter 3 Load Profiling Considering Shape Similarity using Shape-based Clustering.- Chapter 4 Load Classification and Driven Factors Identification based on Ensemble Clustering.- Chapter 5 Power Demand and Probability Density Forecasting based on Deep Learning.- Chapter 6 Load Forecasting of Residential Buildings based on Deep Learning.- Chapter 7 Incentive-based Demand Response with Deep Learning and Reinforcement Learning.- Chapter 8 Residential Electricity Pricing based on Multi-Agent Simulation.- Chapter 9 Integrated Energy Services based on Integrated Demand Response.- Chapter 10 Electric Vehicle Charging Scheduling Considering Different Charging Demands.- Chapter 11 P2P Electricity Trading Pricing in Energy Blockchain Environment.- Chapter 12 Credit-Based P2P Electricity Trading in Energy Blockchain Environment.
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Smart Energy;Energy Management;Demand Side Management;Integrated Energy Services;Smart Grid;Energy Internet;Energy Blockchain;Energy Service;Energy Efficiency;Load Management