- Abagnale C.; Cardone M.; Iodice P.; Strano S.; Terzo M.; Vorraro G. Power requirements and environmental impact of a pedelec. A case study based on real-life applications. Environ. Impact Assess. Rev. 2015, 53, 1-7.
Paper not yet in RePEc: Add citation now
Arias M.B.; Bae S. Electric vehicle charging demand forecasting model based on big data technologies. Appl. Energy 2016, 183, 327-339.
- Box G.E.P.; Cox D.R. An Analysis of Transformations Revisited, Rebutted. J. Am. Stat. Assoc. 1982, 77, 209-210.
Paper not yet in RePEc: Add citation now
Chen L.; Chen Z.; Huang X.; Jin L. A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways. Energies 2016, 9.
Chen L.; Huang X.; Chen Z.; Jin L. Study of a New Quick-Charging Strategy for Electric Vehicles in Highway Charging Stations. Energies 2016, 9. Federal Highway Administration. National Household Travel Survey.
- Chen Z.; Zhang Z.; Zhao J.; Wu B.; Huang X. An Analysis of the Charging Characteristics of Electric Vehicles Based on Measured Data and Its Application. IEEE Access 2018, 6, 24475-24487.
Paper not yet in RePEc: Add citation now
- Flammini M.G.; Prettico G.; Julea A.; Fulli G.; Mazza A.; Chicco G. Statistical characterisation of the real transaction data gathered from electric vehicle charging stations. Electr. Power Syst. Res. 2019, 166, 136-150.
Paper not yet in RePEc: Add citation now
- Iodice P.; Senatore A. Industrial and Urban Sources in Campania, Italy: The Air Pollution Emission Inventory. Energy Environ. 2015, 26, 1305-1317.
Paper not yet in RePEc: Add citation now
- Lojowska A.; Kurowicka D.; Papaefthymiou G.; Van Der Sluis L. Stochastic Modeling of Power Demand Due to EVs Using Copula. IEEE Trans. Power Syst. 2012, 27, 1960-1968.
Paper not yet in RePEc: Add citation now
Luo Y.; Zhu T.; Wan S.; Zhang S.; Li K. Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems. Energy 2016, 97, 359-368.
- Miao P.B.; Yu J.; Liu G.P.; Liang M.; Li W.Y.; Ren Z.Y. Electric public bus load model based on improved kernel density estimation and latin hypercube sampling. Trans. China Electrotech. Soc. 2016, 31, 187-193.
Paper not yet in RePEc: Add citation now
- Rao R.; Cai H.; Xu M. Modeling electric taxis’ charging behavior using real-world data. Int. J. Sustain. Transp. 2018, 12, 452-460.
Paper not yet in RePEc: Add citation now
- Rubinstein R.Y.; Kroese D.P. Simulation and the Monte Carlo Method; John Wiley & Sons: Hoboken, NJ, USA, 2011. Kernel Density Estimation Toolbox.
Paper not yet in RePEc: Add citation now
- Sadeghianpourhamami N.; Refa N.; Strobbe M.; Develder C. Quantitive analysis of electric vehicle flexibility: A data-driven approach. Int. J. Electr. Power Energy Syst. 2018, 95, 451-462.
Paper not yet in RePEc: Add citation now
- Shao Y.C.; Mu Y.F.; Yu X.D.; Dong X.H.; Jia H.J.; Wu J.Z.; Zeng Y. A spatial-temporal charging load forecast and impact analysis method for distribution network using EVs-traffic-distribution model. Proc. CSEE 2017, 37, 5207-5219.
Paper not yet in RePEc: Add citation now
- Silverman B.W. Density Estimation for Statistics and Data Analysis; Springer Science and Business Media LLC: Berlin, Germany, 1986.
Paper not yet in RePEc: Add citation now
- Su J.; Lie T.; Zamora R. Modelling of large-scale electric vehicles charging demand: A New Zealand case study. Electr. Power Syst. Res. 2019, 167, 171-182.
Paper not yet in RePEc: Add citation now
- Sun X.-H.; Yamamoto T.; Morikawa T. Fast-charging station choice behavior among battery electric vehicle users. Transp. Res. Part D Transp. Environ. 2016, 46, 26-39.
Paper not yet in RePEc: Add citation now
- Wang D.; Gao J.; Li P.; Wang B.; Zhang C.; Saxena S. Modeling of plug-in electric vehicle travel patterns and charging load based on trip chain generation. J. Power Sources 2017, 359, 468-479.
Paper not yet in RePEc: Add citation now
- Wang H.L.; Zhang Y.J.; Mao H.P. Charging load forecasting method based on instantaneous charging probability for electric vehicles. Electr. Power Autom. Equip. 2019, 39, 207-213.
Paper not yet in RePEc: Add citation now
- Wang R.; Thakur C.S.; Hamilton T.J.; Tapson J.; Van Schaik A. A neuromorphic hardware architecture using the Neural Engineering Framework for pattern recognition. IEEE Trans. Biomed. Circuits Syst. 2015, 11, 574-584.
Paper not yet in RePEc: Add citation now
- Wei W.; Wu L.; Wang J.; Mei S. Network Equilibrium of Coupled Transportation and Power Distribution Systems. IEEE Trans. Smart Grid 2018, 9, 6764-6779.
Paper not yet in RePEc: Add citation now
- Xie Z. MATLAB Statistic Analysis and Application: 40 Cases Analysis; Beihang University Press: Beijing, China, 2015.
Paper not yet in RePEc: Add citation now
- Xue L. Introduction to Modern Nonparametric Statistics; Science Press: Beijing, China, 2015.
Paper not yet in RePEc: Add citation now
Xydas E.; Marmaras C.; Cipcigan L.M.; Jenkins N.; Carroll S.; Barker M. A data-driven approach for characterising the charging demand of electric vehicles: A UK case study. Appl. Energy 2016, 162, 763-771.
- Yang N.; Huang Y.; Ye X.W.; Li H.S.; Li S.Y.; Dong B.T. Modeling of output correlation of multiple wind farms based on adaptive multivariable nonparametric kernel density estimation. Proc. CSEE 2018, 38, 3805-3812.
Paper not yet in RePEc: Add citation now
- Yang T.Y.; Xu X.X.; Guo Q.L.; Zhang L.; Sun H.B. EV charging behavior analysis and modelling based on mobile crowdsensing data. IET Gener. Transm. Distrib. 2017, 11, 1683-1691.
Paper not yet in RePEc: Add citation now
- Yi T.; Zhang C.; Lin T.; Liu J. Research on the spatial-temporal distribution of electric vehicle charging load demand: A case study in China. J. Clean. Prod. 2020, 242.
Paper not yet in RePEc: Add citation now
- Zhao H.; Yan X.; Ren H. Quantifying flexibility of residential electric vehicle charging loads using non-intrusive load extracting algorithm in demand response. Sustain. Cities Soc. 2019, 50.
Paper not yet in RePEc: Add citation now