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能源经济大数据(英文版)
  • 书号:9787030716422
    作者:刘辉
  • 外文书名:
  • 装帧:圆脊精装
    开本:B5
  • 页数:258
    字数:
    语种:en
  • 出版社:科学出版社
    出版时间:2022-03-10
  • 所属分类:
  • 定价: ¥198.00元
    售价: ¥156.42元
  • 图书介质:
    纸质书

  • 购买数量: 件  可供
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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。本书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。
  全书分为11章:第1章从智慧能源经济学概述进行分析,介绍了能源经济学的能源互联网关键技术,并介绍能源经济大数据需求分析的必要性;第2章介绍石油市场能源经济大数据分析,第3章介绍煤炭市场能源经济大数据分析,第4章风电市场能源经济大数据分析,第5章介绍光伏发电市场能源经济大数据分析,第6章介绍电力市场能源经济大数据分析,第7章介绍用电需求侧节能减排大数据管理,第8章介绍新能源投资全生命周期成本、收益大数据分析,第9章介绍能源经济宏观敏感度分析,第10章介绍能源清洁化转型优化分析,第11章介绍全球能源互联网绿色低碳能源经济创新。
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目录

  • contents
    1 Introduction 1
    1.1 Overview of Research Progress in Energy Economics 1
    1.1.1 History of Energy Economics 1
    1.1.2 Framework for Big Data in Energy Economics 2
    1.1.3 Strategies and Measures for the Development of Big Data in China's Energy Economics 6
    1.1.4 Strategies and Measures for the Development of Big Data in World's Energy Economics 9
    1.2 Key Technologies of Energy Internet in Energy Economics 14
    1.2.1 Concept of Energy Internet 14
    1.2.2 Reasons for Building a Global Energy Internet 16
    1.2.3 Key Technologies of Energy Internet 17
    1.3 Big Data Demand Analysis for Energy Economics 20
    1.3.1 Summary of Key Technical Tools 21
    1.3.2 Application Scenarios of Big Data Technology 29
    1.4 Scope of This Book 31
    References 34
    2 Big Data Analysis of Energy Economics in Oil Market 43
    2.1 Introduction 43
    2.2 Influencing Factors Analysis of Oil Prices 45
    2.2.1 Data Description of Crude Oil Prices Influencing Factors 46
    2.2.2 Correlation Analysis of the Factors Affecting Crude Oil Prices 46
    23 Big Data Forecasting of Oil Prices 50
    2.3.1 Base Forecasting Models 50
    2.3.2 Crude Oil Futures and Spot Prices Time Series Forecasting Model 53
    23.3 Performance Metrics 54
    2.3.4 Results and Discussions 55
    2.4 Econometric Analysis of Oil Prices 57
    2.4.1 Energy Economic Analysis of Crude Oil Market 57
    2.4.2 Big Data Prediction Technology 61
    2.4.3 Policies and Recommendations 62
    2.5 Conclusions 62
    References 64
    3 Big Data Analysis of Energy Economics in Coal Market 67
    3.1 Introduction 67
    3.2 Influencing Factors Analysis of Coal Prices 68
    3.2.1 Data Description of Coal Prices Inluencing Factors 69
    3.2.2 Correlation Analysis of the Factors Affecting Coal Prices 72
    3.3 Big Data Forecasting of Coal Prices 73
    3.3.1 The Components of the Proposed Model 73
    3.3.2 Multi-factor Coal Price Hybrid Forecasting Model 80
    3.3.3 Performance Metrics 81
    3.3.4 Results and Discussions 81
    3.4 Econometic Analysis of Coal Prices 86
    3.4.1 Energy Economic Analysis of the Coal Market 86
    3.4.2 Big Data Prediction Technology 87
    3.4.3 Policies and Recommendations 88
    3.5 Conclusions 91
    References 92
    4 Big Data Analysis of Energy Economics in Wind Power Market 95
    4.1 Introduction 95
    4.2 Muli-temporal and Spatial Scale Wind Power Big Data Forecasting 96
    4.2.1 Description of Original Wind Dataset 96
    4.2.2 Framework of Wind Power Forecasting Models 97
    4.2.3 Analysis of Wind Power Forecasting Models 98
    4.3 Conversion Eficiency of Wind Power Energy 104
    4.4 Market Economy Analysis of Wind Power Application 107
    4.4.1 Market Economy Analysis of Wind Power Application in China 107
    4.4.2 Market Economy Analysis of Wind Power Application in America 111
    4.4.3 Market Economy Analysis of Wind Power Application in Europe 112
    4.5 Conclusions 113
    References 114
    5 Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market 117
    5.1 Introduction 117
    5.2 Big Data Forecasting of Photovoltaice Power Generation 117
    5.2.1 Big Data Processing Engines 118
    5.2.2 Forecasting Strategy and Methods 119
    5.23 Forecasting Models 120
    5.3 Photovoltaic Power Consumption by Small and Medium Sized Users 123
    5.3.1 Dataset Descripion 123
    5.3.2 Experiments 123
    5.4 Photovolaic Power Consumption in Urtban Public Areas 126
    5.4.1 Dataset Descripion 127
    5.4.2 Experiments 128
    5.5 Market Economy Analysis of Photovoltaic Systems 129
    5.5.1 Dispatch of Photovoltaic Power Integration 129
    5.5.2 Optimization Model of Photovoltaic Power Integration 130
    5.5.3 Single- and Multi objective Optimization Algorithms 133
    5.6 Conclusions 135
    References 136
    6 Big Data Analysis of Power Market Energy Economics 137
    6.1 Introduction 137
    6.2 Big Data Forecasting of Urban Electricity Price 138
    6.2.1 Electricity Price Forecasting Method Based on Empirical Mode Decomposition and Extreme Learning Machine 139
    6.2.2 Electicity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Bclief Nelwork 143
    6.2.3 Big Data Processing of Electricily Price Based on Empirical Wavelet Transfom and Long Short-Term Memory Network 150
    6.3 Correlation Analysis of Urban Energy Consumption and Economic Growth 155
    6.3.1 Grey Correlation Model in the Energy Economy 155
    6.3.2 Grey Corelation Analysis of Economic Growth and Energy Consumption Varicties 156
    6.3.3 Grey Coelation Analysis of Economic Growth and Energy Consumption Industrial Structure 157
    6.4 Metering Charge Adjustment Analysis of City Electicity Prices 159
    6.4.1 Background of the K means Algorithm for Characteristic Analysis of Electricity Price 159
    6.4.2 Analysis of User Eletricity Price Consumption Characteristics Based on the K means Algorithm 161
    6.4.3 Optimization Design of Residential Stepped Electricity Price 162
    6.5 Conclusions 165
    References 166
    7 Big Data Mangmente ont Smart City Energy Conservation and Eminssion Reduction 169
    7.1 Introduction 169
    7.1.1 Background and Introduction 169
    7.1.2 Dataset Decription 170
    7.2 No-intnusive Load Identification of Electrical Equipment 171
    7.2.1 Nonintusive Load Identification Based on Signal Decomposition 172
    7.2.2 Non-intrusive Load Identification Based on Electrical Switching Event Classification 177
    7.2.3 Non-intrusive Load Identification Based on Multi-label Classification 184
    7.3 Guide to Smart City Electricity Behavior 187
    7.3.1 Smart Grid Planning of a City 187
    7.3.2 Urban Public Electricity Behavior Research 191
    7.4 Analysis of Energy Conservation and Emission Reduction of Smart Cities 192
    7.5 Conclusions 193
    References 194
    8 Optimization Analysis of Clean Energy Transformation 197
    8.1 Introduction 197
    8.1.1 Global Status of Clean Energy Development 197
    8.1.2 International Experience in the Transformation of Clean Energy Industry 200
    8.2 Efficiency Analysis of Energy Utilization Under Diversified Development 202
    8.2.1 Evaluation Indexes and Methods of Energy Efficiency 202
    8.2.2 Analysis of Influencing Factors and Mechanism of Energy Efficiency 203
    8.2.3 International Comparative Analysis of Energy Efficiency 207
    8.3 Analysis of Reasonable Energy Consumption Patterns 211
    8.3.1 Challenges Facing Energy Consumption 211
    8.3.2 Analysis of Key Factors Affecting Clean Energy Consumption 212
    8.3.3 Reform Strategy of Clean Energy Consumption Patterns 216
    8.4 Economic Analysis of Clean Energy Transformation 219
    8.4.1 Mechanisms for Developing Clean Energy to Affect Economic Growth 220
    8.4.2 Ways to Promote a Low-Carbon Economy Based on Clean Energy 227
    8.5 Conclusions 229
    References 229
    9 Global Energy Internet Green and Low-Carbon Energy Economic Innovation 233
    9.1 Intoduction 233
    9.2 Reform and Innovation of the New Energy System Under the Energy Internet 236
    9.2.1 Comparison of Convenional Energy System and New Energy System 236
    9.2.2 Production in New Energy System 237
    9.2.3 Supply and Marketing in New Energy System 240
    9.3 Enery Saving and Enssis Redution Under the Encrey Internet 243
    9.3.1 Energy Saving and Emissn Reducion in Production Process 244
    9.3.2 Energy Saving and Enision Reduction in Supply and Marketing Process 246
    9.4 Heally Casructo of tbe Eclogia Evinomen Under the Energy Internet 249
    9.4.1 Land Ecolgy and Povoltic Power 249
    9.4.2 Hydropower and Ecology 251
    9.4.3 Biological Energy and Eecology 252
    9.5 Conclusions 253
    References 255
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