This book combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost-benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure. This book provides an important reference for professionals in related fields such as smart energy, smart economy, energy Internet, artificial intelligence, energy economics and policy.

Autorentext

Dr. Hui Liu is a Full Professor of Artificial Intelligence, Smart Cities and Smart Energy at Central South University (CSU), China. Prof. Liu is the director of Institute of Artificial Intelligence and Robotics at CSU. He received double Ph.D degrees from Central South University (China) in 2011 and University of Rostock (Germany) in 2013, respectively. He received habilitation degree from University of Rostock in 2016. He was appointed as the BMBF junior group leader by the Ministry of Education and Research of Germany at University of Rostock since January, 2015 until December 2016. Dr. Nikolaos Nikitas is an Associate Professor in Structural Engineering, Data Sciences and Wind Energy at University of Leeds, UK. Prof. Nikitas is the data centric engineering group leader at The Alan Turing Institute, UK. He received double Ph.D degrees from The University of Edinburgh in 2008 and University of Bristol in 2011, respectively. Dr. Yanfei Li is an Associate Professor in Artificial Intelligence, Smart Agriculture and Smart Energy at Hunan Agricultural University (HAU), China. Prof. Li is the director of Institute of Artificial Intelligence at HAU. She received Ph.D degree from University of Rostock (Germany) in 2014 then worked as a postdoctoral fellow at University of Rostock in 2015. Mr. Rui Yang is a Ph.D Candidate in Smart Energy Systems at Central South University (CSU), China.

Inhalt

Chapter 1 Introduction1.1 Overview of Research Progress in Energy Economics1.2 Key Technologies of Energy Internet in Energy Economics1.3 Big Data Demand Analysis for Energy Economics1.4 Scope of This Book1.5 ReferencesChapter 2 Big Data Analysis of Energy Economics in Oil Market 2.1 Introduction2.2 Influencing Factors Analysis of Oil Prices2.3 Big Data Forecasting of Oil Prices2.4 Econometric Analysis of Oil Prices2.5 Conclusions2.6 ReferencesChapter 3 Big Data Analysis of Energy Economics in Coal Market3.1 Introduction3.2 Influencing Factors Analysis of Coal Prices3.3 Big Data Forecasting of Coal Prices3.4 Econometric Analysis of Coal Prices3.5 Conclusions3.6 ReferencesChapter 4 Big Data Analysis of Energy Economics in Wind Power Market4.1 Introduction4.2 Multi-Temporal and Spatial Scale Wind Power Big Data Forecasting4.3 Conversion Efficiency of Wind Power Energy 4.4 Market Economy Analysis of Wind Power Application4.5 Conclusions4.6 ReferencesChapter 5 Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market5.1 Introduction5.2 Big Data Forecasting of Photovoltaic Power Generation5.3 Photovoltaic Power Consumption by Small and Medium-sized Users5.4 Photovoltaic Power Consumption in Urban Public Areas5.5 Market Economy Analysis of Photovoltaic Systems5.6 Conclusions5.7 ReferencesChapter 6 Big Data Analysis of Energy Economics in Power Market 6.1 Introduction6.2 Big Data Forecasting of Urban Electricity Prices6.3 Correlation Analysis of Urban Energy Consumption and Economic Growth6.4 Metering Charge Adjustment Analysis of City Electricity Prices6.5 Conclusions6.6 ReferencesChapter 7 Big Data Management of Energy Conservation and Emission Reduction in Smart Cities7.1 Introduction7.2 Non-intrusive Identification of Smart Electrical Equipment7.3 Electricity Consumption Behavior Guidance in Smart Cities 7.4 Effectiveness Analysis of Energy Conservation and Emission Reduction in Smart Cities7.5 Conclusions7.6 ReferencesChapter 8 Optimization Analysis of Clean Energy Transformation8.1 Introduction8.2 Efficiency Analysis of Energy Utilization Under Diversified Development8.3 Analysis of Reasonable Energy Consumption Patterns8.4 Economic Analysis of Clean Energy Transformation8.5 Conclusions8.6 ReferencesChapter 9 Global Energy Internet: Green and Low-Carbon Energy Economic Innovation9.1 Introduction9.2 Reform and Innovation of the New Energy System Under the Energy Internet9.3 Energy Saving and Emission Reduction Under the Energy Internet9.4 Healthy Construction of the Ecological Environment Under the Energy Internet9.5 Conclusions9.6 References