Titlebook: Big Data in Energy Economics; Hui Liu,Nikolaos Nikitas,Rui Yang Book 2022 Science Press 2022 Energy Economy.Big Data Analysis.Time Series

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Recess

Big Data Analysis of Energy Economics in Oil Market, economic significance and social value of forecasting crude oil prices are first introduced. Then the factors that affect the fluctuation in crude oil prices are expounded, including the relationship between supply and demand, economic development, policy formulation, global emergencies, etc. Next,

渐变

Big Data Analysis of Energy Economics in Coal Market,ect the country‘s investment, consumption, import and export, and overall economic development. This chapter introduces the important role of coal in the field of energy economics and analyzes the factors that influence coal price fluctuations. Then, through correlation analysis, this chapter select

Mercantile

Big Data Analysis of Energy Economics in Wind Power Market,f wind energy. The wind power market also contains huge development prospects and opportunities. This chapter focuses on wind energy to carry out big data analysis of energy economy. To realize the trend analysis of wind energy, this chapter first proposes a spatial scale wind energy prediction fram

杀子女者

Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market, help for alleviating the energy crisis. Developing photovoltaic power generation can exploit the untapped and abundant solar energy resources and contribute to regional economic development. However, photovoltaic power generation systems still face many challenges such as randomness, uncertainty, a

CAND

Big Data Analysis of Power Market Energy Economics,s in the city electricity price, the city electricity price metering charge adjustment scheme is put forward. Finally, the feasibility of the method is verified by experiments, and the experimental results are summarized. Compared with empirical mode decomposition and wavelet packet decomposition, t

Ingratiate

Big Data Management of Smart City Energy Conservation and Emission Reduction,sion reduction are closely related to the sustainable development of the urban economy. Load identification technology is one of the core technical difficulties to be solved in realizing the overall layout planning of the smart power grid. Statistics show that with the information provided by the no

珐琅

Optimization Analysis of Clean Energy Transformation,n efficiency, optimizing consumption patterns, and cutting emissions, has become an inevitable choice for countries around the world to promote sustainable economic development. This chapter summarizes the effective practices of developed countries in promoting clean energy transformation. Combined

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