Big Data in Energy Economics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer
2022
|
| Schriftenreihe: | Management for Professionals Series
|
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (275 Seiten) |
| ISBN: | 9789811689659 |
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| 505 | 8 | |a Intro -- Preface -- Contents -- Nomenclature -- List of Figures -- List of Tables -- 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 -- 2.3 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 -- 2.3.3 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 Influencing 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 | |
| 505 | 8 | |a 3.3.2 Multi-factor Coal Price Hybrid Forecasting Model -- 3.3.3 Performance Metrics -- 3.3.4 Results and Discussions -- 3.4 Econometric 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 Multi-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 Efficiency 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 Photovoltaic Power Generation -- 5.2.1 Big Data Processing Engines -- 5.2.2 Forecasting Strategy and Methods -- 5.2.3 Forecasting Models -- 5.3 Photovoltaic Power Consumption by Small and Medium-Sized Users -- 5.3.1 Dataset Description -- 5.3.2 Experiments -- 5.4 Photovoltaic Power Consumption in Urban Public Areas -- 5.4.1 Dataset Description -- 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 | |
| 505 | 8 | |a 6.2.1 Electricity Price Forecasting Method Based on Empirical Mode Decomposition and Extreme Learning Machine -- 6.2.2 Electricity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Belief Network -- 6.2.3 Big Data Processing of Electricity Price Based on Empirical Wavelet Transform 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 Correlation Analysis of Economic Growth and Energy Consumption Varieties -- 6.3.3 Grey Correlation Analysis of Economic Growth and Energy Consumption Industrial Structure -- 6.4 Metering Charge Adjustment Analysis of City Electricity Prices -- 6.4.1 Background of the K-means Algorithm for Characteristic Analysis of Electricity Price -- 6.4.2 Analysis of User Electricity 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 | |
| 505 | 8 | |a 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 Internet -- 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 | |
| 650 | 4 | |a Big data | |
| 700 | 1 | |a Nikitas, Nikolaos |e Sonstige |4 oth | |
| 700 | 1 | |a Li, Yanfei |e Sonstige |4 oth | |
| 700 | 1 | |a Yang, Rui |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Liu, Hui |t Big Data in Energy Economics |d Singapore : Springer,c2022 |z 9789811689642 |
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Datensatz im Suchindex
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| author | Liu, Hui |
| author_facet | Liu, Hui |
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| author_sort | Liu, Hui |
| author_variant | h l hl |
| building | Verbundindex |
| bvnumber | BV048920929 |
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| contents | Intro -- Preface -- Contents -- Nomenclature -- List of Figures -- List of Tables -- 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 -- 2.3 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 -- 2.3.3 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 Influencing 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 Econometric 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 Multi-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 Efficiency 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 Photovoltaic Power Generation -- 5.2.1 Big Data Processing Engines -- 5.2.2 Forecasting Strategy and Methods -- 5.2.3 Forecasting Models -- 5.3 Photovoltaic Power Consumption by Small and Medium-Sized Users -- 5.3.1 Dataset Description -- 5.3.2 Experiments -- 5.4 Photovoltaic Power Consumption in Urban Public Areas -- 5.4.1 Dataset Description -- 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 Electricity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Belief Network -- 6.2.3 Big Data Processing of Electricity Price Based on Empirical Wavelet Transform 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 Correlation Analysis of Economic Growth and Energy Consumption Varieties -- 6.3.3 Grey Correlation Analysis of Economic Growth and Energy Consumption Industrial Structure -- 6.4 Metering Charge Adjustment Analysis of City Electricity Prices -- 6.4.1 Background of the K-means Algorithm for Characteristic Analysis of Electricity Price -- 6.4.2 Analysis of User Electricity 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 Internet -- 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 |
| ctrlnum | (ZDB-30-PQE)EBC6885490 (ZDB-30-PAD)EBC6885490 (ZDB-89-EBL)EBL6885490 (OCoLC)1296427254 (DE-599)BVBBV048920929 |
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| dewey-search | 333.79028557 |
| dewey-sort | 3333.79028557 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>08896nmm a2200469zc 4500</leader><controlfield tag="001">BV048920929</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230502s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789811689659</subfield><subfield code="9">978-981-1689-65-9</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC6885490</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PAD)EBC6885490</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL6885490</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1296427254</subfield></datafield><datafield tag="035" 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code="c">©2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (275 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Management for Professionals Series</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Intro -- Preface -- Contents -- Nomenclature -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 Overview of Research Progress in Energy Economics -- 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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 Multi-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 Efficiency 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 Photovoltaic Power Generation -- 5.2.1 Big Data Processing Engines -- 5.2.2 Forecasting Strategy and Methods -- 5.2.3 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| id | DE-604.BV048920929 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:55:16Z |
| indexdate | 2024-07-10T09:49:54Z |
| institution | BVB |
| isbn | 9789811689659 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034185020 |
| oclc_num | 1296427254 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (275 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| record_format | marc |
| series2 | Management for Professionals Series |
| spelling | Liu, Hui Verfasser aut Big Data in Energy Economics Singapore Springer 2022 ©2022 1 Online-Ressource (275 Seiten) txt rdacontent c rdamedia cr rdacarrier Management for Professionals Series Description based on publisher supplied metadata and other sources Intro -- Preface -- Contents -- Nomenclature -- List of Figures -- List of Tables -- 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 -- 2.3 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 -- 2.3.3 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 Influencing 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 Econometric 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 Multi-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 Efficiency 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 Photovoltaic Power Generation -- 5.2.1 Big Data Processing Engines -- 5.2.2 Forecasting Strategy and Methods -- 5.2.3 Forecasting Models -- 5.3 Photovoltaic Power Consumption by Small and Medium-Sized Users -- 5.3.1 Dataset Description -- 5.3.2 Experiments -- 5.4 Photovoltaic Power Consumption in Urban Public Areas -- 5.4.1 Dataset Description -- 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 Electricity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Belief Network -- 6.2.3 Big Data Processing of Electricity Price Based on Empirical Wavelet Transform 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 Correlation Analysis of Economic Growth and Energy Consumption Varieties -- 6.3.3 Grey Correlation Analysis of Economic Growth and Energy Consumption Industrial Structure -- 6.4 Metering Charge Adjustment Analysis of City Electricity Prices -- 6.4.1 Background of the K-means Algorithm for Characteristic Analysis of Electricity Price -- 6.4.2 Analysis of User Electricity 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 Internet -- 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 Big data Nikitas, Nikolaos Sonstige oth Li, Yanfei Sonstige oth Yang, Rui Sonstige oth Erscheint auch als Druck-Ausgabe Liu, Hui Big Data in Energy Economics Singapore : Springer,c2022 9789811689642 |
| spellingShingle | Liu, Hui Big Data in Energy Economics Intro -- Preface -- Contents -- Nomenclature -- List of Figures -- List of Tables -- 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 -- 2.3 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 -- 2.3.3 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 Influencing 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 Econometric 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 Multi-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 Efficiency 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 Photovoltaic Power Generation -- 5.2.1 Big Data Processing Engines -- 5.2.2 Forecasting Strategy and Methods -- 5.2.3 Forecasting Models -- 5.3 Photovoltaic Power Consumption by Small and Medium-Sized Users -- 5.3.1 Dataset Description -- 5.3.2 Experiments -- 5.4 Photovoltaic Power Consumption in Urban Public Areas -- 5.4.1 Dataset Description -- 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 Electricity Price Forecasting Method Based on Wavelet Packet Decomposition and Deep Belief Network -- 6.2.3 Big Data Processing of Electricity Price Based on Empirical Wavelet Transform 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 Correlation Analysis of Economic Growth and Energy Consumption Varieties -- 6.3.3 Grey Correlation Analysis of Economic Growth and Energy Consumption Industrial Structure -- 6.4 Metering Charge Adjustment Analysis of City Electricity Prices -- 6.4.1 Background of the K-means Algorithm for Characteristic Analysis of Electricity Price -- 6.4.2 Analysis of User Electricity 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 Internet -- 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 Big data |
| title | Big Data in Energy Economics |
| title_auth | Big Data in Energy Economics |
| title_exact_search | Big Data in Energy Economics |
| title_exact_search_txtP | Big Data in Energy Economics |
| title_full | Big Data in Energy Economics |
| title_fullStr | Big Data in Energy Economics |
| title_full_unstemmed | Big Data in Energy Economics |
| title_short | Big Data in Energy Economics |
| title_sort | big data in energy economics |
| topic | Big data |
| topic_facet | Big data |
| work_keys_str_mv | AT liuhui bigdatainenergyeconomics AT nikitasnikolaos bigdatainenergyeconomics AT liyanfei bigdatainenergyeconomics AT yangrui bigdatainenergyeconomics |