## 2 Literature Review
### Bibliometric Review
[CrossRef][PERSON]; [PERSON]; [PERSON]; [PERSON] Integrated energy systems of data centers and smart grids: State-of-the-art and future opportunities. _Appl. Energy_**2021**, _301_, 117474. [CrossRef]
* (4) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A review of electricity demand forecasting in low and middle income countries: The demand determinants and horizons. _Sustainability_**2020**, _12_, 5931. [CrossRef]
* (5) [PERSON]; [PERSON] A literature review on the charging behaviour of private electric vehicles. _Appl. Sci._**2023**, _13_, 12877. [CrossRef]
* (6) [PERSON]; [PERSON] The impact of rapid urbanization on residential energy consumption in China. _PLoS ONE_**2022**, _17_, e0270226. [CrossRef] [PubMed]
* (7) [PERSON] [PERSON]; [PERSON]; [PERSON] Electricity consumption forecasting in Brazil: A spatial econometrics approach. _Energy_**2017**, _126_, 124-131. [CrossRef]
* (8) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A bottom-up methodology for long term electricity consumption forecasting of an industrial sector-Application to pulp and paper sector in Brazil. _Energy_**2018**, _144_, 1107-1118. [CrossRef]
* (9) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] Forecasting residential electricity consumption: A bottom-up approach for Brazil by region. _Energyffic._**2020**, _13_, 911-934. [CrossRef]
* (10) [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Statistical and artificial neural networks models for electricity consumption forecasting in the Brazilian industrial sector. _Energies_**2022**, _15_, 588. [CrossRef]
* (11) [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Analysis of time series models for Brazilian electricity demand forecasting. _Energy_**2022**, _247_, 123483. [CrossRef]
* (12) [PERSON]; [PERSON]; [PERSON] Machine learning models for forecasting power electricity consumption using a high dimensional dataset. _Expert Syst. Appl._**2022**, _187_, 115917. [CrossRef]
* (13) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] _Time Series Analysis: Forecasting and Control_; Wiley: San Francisco, CA, USA, 1976. * (14) [PERSON]; [PERSON] Forecasting at scale. _Am. Stat._**2018**, _72_, 37-45. [CrossRef]
* (15) [PERSON] Forecasting sales by exponentially weighted moving averages. _Manag. Sci._**1960**, \(6\), 324-342. [CrossRef]
* (16) [PERSON]; [PERSON]; [PERSON] Forecasting time series with complex seasonal patterns using exponential smoothing. _J. Am. Stat. Assoc._**2011**, _106_, 1513-1527. [CrossRef]
* (17) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Maximum power demand prediction using fbprophet with adaptive Kalman filtering. _IEEE Access_**2020**, \(8\), 19236-19247. [CrossRef]
* (18) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India. _Energy Policy_**2022**, _168_, 113097. [CrossRef]
* (19) [PERSON]; [PERSON] Forecasting methods in energy planning models. _Renew. Sustain. Energy Rev._**2018**, _88_, 297-325. [CrossRef]
* (20) [PERSON]; [PERSON] Electricity price forecasting in the Danish day-ahead market using the TBATS, ANN and ARIMA methods. _Energies_**2019**, _12_, 928. [CrossRef]
* (21) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Forecasting peak energy demand for smart buildings. _J. Supercomput._**2021**, _77_, 6356-6380. [CrossRef]
* (22) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. Automatic Literature Mapping Selection: Classification of Papers on Industry Productivity. _Appl. Sci._**2024**, _14_, 3679. [CrossRef]
* (23) [PERSON]; [PERSON]; [PERSON]; [PERSON] Energy Demand Forecasting and Optimizing Electric Systems for Developing Countries: A Systematic Review. _IEEE Access_**2023**, _11_, 39751-39775. [CrossRef]
* (24) [PERSON]; [PERSON]; [PERSON]; [PERSON] An online transfer learning model for wind turbine power prediction based on spatial feature construction and system-wide update. _Appl.