@article{1444361,
      recid = {1444361},
      author = {Liu, Hui, and Nikitas, Nikolaos. and Li, Yanfei. and Yang,  Rui.},
      title = {Big data in energy economics /},
      publisher = {Springer,},
      address = {Singapore :},
      pages = {1 online resource (275 pages)},
      year = {2022},
      abstract = {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 costbenefit 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.},
      url = {http://library.usi.edu/record/1444361},
      doi = {https://doi.org/10.1007/978-981-16-8965-9},
}