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能源經濟大數據(英文版)(精)

  • 作者:劉輝//(希)尼古拉斯 尼基塔斯//李燕飛//楊睿
  • 出版社:科學
  • ISBN:9787030716422
  • 出版日期:2022/01/01
  • 裝幀:精裝
  • 頁數:258
人民幣:RMB 198 元      售價:
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內容大鋼
    能源是人類社會賴以生存和發展的重要物質基礎,能源的生產消費對經濟發展起到至關重要的作用,而能源問題也成為全世界矚目的焦點。能源經濟學正是在這種背景下發展起來的一門年輕的科學。《能源經濟大數據(英文版)》結合能源互聯網以及大數據建模技術在能源經濟學中的應用,全面介紹了智慧能源經濟、大數據建模的相關理論、關鍵技術和應用實例。

作者介紹
劉輝//(希)尼古拉斯 尼基塔斯//李燕飛//楊睿

目錄
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
    6.2.3  Big Data Processing of Electricily Price Based on Empirical Wavelet Transfom and Long Short-Term Memory Network
  6.3  Correlation Analysis of Urban Energy Consumption and Economic Growth
    6.3.1  Grey Correlation Model in the Energy Economy
    6.3.2  Grey Corelation Analysis of Economic Growth and Energy Consumption Varicties
    6.3.3  Grey Coelation Analysis of Economic Growth and Energy Consumption Industrial Structure
  6.4  Metering Charge Adjustment Analysis of City Electicity Prices
    6.4.1  Background of the K means Algorithm for Characteristic Analysis of Electricity Price
    6.4.2  Analysis of User Eletricity Price Consumption Characteristics Based on the K means Algorithm
    6.4.3  Optimization Design of Residential Stepped Electricity Price
  6.5  Conclusions
References
7 Big Data Management of Smart City Energy Conservation
and Emission Reduction
  7.1  Introduction
    7.1.1  Background and Introduction
    7.1.2  Dataset Description
  7.2  Non-intrusive Load Identification of Electrical Equipment

    7.2.1  Nonintrusive Load Identification Based on Signal Decomposition
    7.2.2  Non-intrusive Load Identification Based on Electrical Switching Event Classification
    7.2.3  Non-intrusive Load Identification Based on Multi-label Classification
  7.3  Guide to Smart City Electricity Behavior
    7.3.1  Smart Grid Planning of a City
    7.3.2  Urban Public Electricity Behavior Research
  7.4  Analysis of Energy Conservation and Emission Reduction of Smart Cities
  7.5  Conclusions
References
8 Optimization Analysis of Clean Energy Transformation
  8.1  Introduction
    8.1.1  Global Status of Clean Energy Development
    8.1.2  International Experience in the Transformation of Clean Energy Industry
  8.2  Efficiency Analysis of Energy Utilization Under Diversified Development
    8.2.1  Evaluation Indexes and Methods of Energy Efficiency
    8.2.2  Analysis of Influencing Factors and Mechanism of Energy Efficiency
    8.2.3  International Comparative Analysis of Energy Efficiency
  8.3  Analysis of Reasonable Energy Consumption Patterns
    8.3.1  Challenges Facing Energy Consumption
    8.3.2  Analysis of Key Factors Affecting Clean Energy Consumption
    8.3.3  Reform Strategy of Clean Energy Consumption Patterns
  8.4  Economic Analysis of Clean Energy Transformation
    8.4.1  Mechanisms for Developing Clean Energy to Affect Economic Growth
    8.4.2  Ways to Promote a Low-Carbon Economy Based on Clean Energy
  8.5  Conclusions
  References
9 Global Energy Internet Green and Low-Carbon Energy
  Economic Innovation
  9.1  Introduction
  9.2  Reform and Innovation of the New Energy System Under the Energy Internet
    9.2.1  Comparison of Conventional Energy System and New Energy System
    9.2.2  Production in New Energy System
    9.2.3  Supply and Marketing in New Energy System
  9.3  Energy Saving and Emission Reduction Under the Energy Intemet
    9.3.1  Energy Saving and Emission Reduction in Production Process
    9.3.2  Energy Saving and Emission Reduction in Supply and Marketing Process
  9.4  Healthy Construction of the Ecological Environment Under the Energy Internet
    9.4.1  Land Ecology and Photovoltaic Power
    9.4.2  Hydropower and Ecology
    9.4.3  Biological Energy and Ecology
  9.5  Conclusions
  References

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