能源是人类社会赖以生存和发展的重要物质基础，能源的生产消费对经济发展起到至关重要的作用，而能源问题也成为全世界瞩目的焦点。能源经济学正是在这种背景下发展起来的一门年轻的科学。《能源经济大数据（英文版）》结合能源互联网以及大数据建模技术在能源经济学中的应用，全面介绍了智慧能源经济、大数据建模的相关理论、关键技术和应用实例。

1 Introduction
1.1 Overview of Research Progress in Energy Economics
1.1.1 History of Energy Economics
1.1.2 Framework for Big Data in Energy Economics
1.1.3 Strategies and Measures for the Development of Big Data in China's Energy Economics
1.1.4 Strategies and Measures for the Development of Big Data in World's Energy Economics
1.2 Key Technologies of Energy Internet in Energy Economics
1.2.1 Concept of Energy Internet
1.2.2 Reasons for Building a Global Energy Internet
1.2.3 Key Technologies of Energy Internet
1.3 Big Data Demand Analysis for Energy Economics
1.3.1 Summary of Key Technical Tools
1.3.2 Application Scenarios of Big Data Technology
1.4 Scope of This Book
References
2 Big Data Analysis of Energy Economics in Oil Market
2.1 Introduction
2.2 Influencing Factors Analysis of Oil Prices
2.2.1 Data Description of Crude Oil Prices Influencing Factors
2.2.2 Correlation Analysis of the Factors Affecting Crude Oil Prices
23 Big Data Forecasting of Oil Prices
2.3.1 Base Forecasting Models
2.3.2 Crude Oil Futures and Spot Prices Time Series Forecasting Model
23.3 Performance Metrics
2.3.4 Results and Discussions
2.4 Econometric Analysis of Oil Prices
2.4.1 Energy Economic Analysis of Crude Oil Market
2.4.2 Big Data Prediction Technology
2.4.3 Policies and Recommendations
2.5 Conclusions
References
3 Big Data Analysis of Energy Economics in Coal Market
3.1 Introduction
3.2 Influencing Factors Analysis of Coal Prices
3.2.1 Data Description of Coal Prices Inluencing Factors
3.2.2 Correlation Analysis of the Factors Affecting Coal Prices
3.3 Big Data Forecasting of Coal Prices
3.3.1 The Components of the Proposed Model
3.3.2 Multi-factor Coal Price Hybrid Forecasting Model
3.3.3 Performance Metrics
3.3.4 Results and Discussions
3.4 Econometic Analysis of Coal Prices
3.4.1 Energy Economic Analysis of the Coal Market
3.4.2 Big Data Prediction Technology
3.4.3 Policies and Recommendations
3.5 Conclusions
References
4 Big Data Analysis of Energy Economics in Wind Power Market
4.1 Introduction
4.2 Muli-temporal and Spatial Scale Wind Power Big Data Forecasting
4.2.1 Description of Original Wind Dataset
4.2.2 Framework of Wind Power Forecasting Models
4.2.3 Analysis of Wind Power Forecasting Models
4.3 Conversion Eficiency of Wind Power Energy
4.4 Market Economy Analysis of Wind Power Application
4.4.1 Market Economy Analysis of Wind Power Application in China
4.4.2 Market Economy Analysis of Wind Power Application in America
4.4.3 Market Economy Analysis of Wind Power Application in Europe
4.5 Conclusions
References
5 Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market
5.1 Introduction
5.2 Big Data Forecasting of Photovoltaice Power Generation
5.2.1 Big Data Processing Engines
5.2.2 Forecasting Strategy and Methods
5.23 Forecasting Models
5.3 Photovoltaic Power Consumption by Small and Medium Sized Users
5.3.1 Dataset Descripion
5.3.2 Experiments
5.4 Photovolaic Power Consumption in Urtban Public Areas
5.4.1 Dataset Descripion
5.4.2 Experiments
5.5 Market Economy Analysis of Photovoltaic Systems
5.5.1 Dispatch of Photovoltaic Power Integration
5.5.2 Optimization Model of Photovoltaic Power Integration
5.5.3 Single- and Multi objective Optimization Algorithms
5.6 Conclusions
References
6 Big Data Analysis of Power Market Energy Economics
6.1 Introduction
6.2 Big Data Forecasting of Urban Electricity Price
6.2.1 Electricity Price Forecasting Method Based on Empirical Mode Decomposition and Extreme Learning Machine
6.2.2 Electicity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Bclief Nelwork
6.