Accès libre

Benefit evaluation analysis of new energy power consumption information collection with basic steady-state harmonic characteristics

À propos de cet article

Citez

Wan, Z., Li, J., & Yan, G. (2018). Monitoring and diagnosis process of abnormal consumption on smart power grid. Neural Computing and Applications, 30(1), 1-8. Search in Google Scholar

Wan, J. (2018). Monitoring and diagnosis process of abnormal consumption on smart power grid. Neural computing & applications, 30(1). Search in Google Scholar

Ali, S., Razman, M. R., Awang, A., Asyraf, M., & Lawrence, R. J. (2021). Critical determinants of household electricity consumption in a rapidly growing city. Sustainability, 13(8), 4441. Search in Google Scholar

Liu, X., Sun, T., Feng, Q., & Zhang, D. (2020). Dynamic nonlinear influence of urbanization on china’s electricity consumption: evidence from dynamic economic growth threshold effect. Energy, 196(Apr.1), 117187.1-117187.11. Search in Google Scholar

Grycan, W. (2020). Legislative support for improving sustainable and smart electricity consumption in polish residential sector. Journal of Cleaner Production, 266, 121995. Search in Google Scholar

Romero-Jordán, & PD Río. (2022). Analysing the drivers of the efficiency of households in electricity consumption. Energy Policy, 164, 112828-. Search in Google Scholar

Yang, T., Ren, M., & Zhou, K. (2018). Identifying household electricity consumption patterns: a case study of kunshan, china. Renewable & Sustainable Energy Reviews, 91(aug.), 861-868. Search in Google Scholar

Jiang, Y., Yang, J., Wang, C., & Cao, Y. (2020). Electricity optimal scheduling strategy considering multiple parks shared energy in the absence of grid power supply. International Transactions on Electrical Energy Systems, 30(12). Search in Google Scholar

Song Ding, Hipel, K. W., & Dang], Y. G. (2018). Forecasting china’s electricity consumption using a new grey prediction model. Energy. Search in Google Scholar

Zhou, Kaile, Yang, Shanlin, Cheng, & Chen, et al. (2017). Data quality of electricity consumption data in a smart grid environment. Renewable & sustainable energy reviews, 75(Aug.), 98-105. Search in Google Scholar

Shao, X., Kim, C. S., Sontakke, P., Energies, & Sciubba, E. (2020). Accurate deep model for electricity consumption forecasting using multi-channel and multi-scale feature fusion cnn–lstm. Energies, 13(Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids)), 1881. Search in Google Scholar

Dai, J. (2023). Management and control optimization based on deep learning model. 3c Empresa: investigación y pensamiento crítico, 12(1), 37-49. Search in Google Scholar

Alexander, T., Per, N., & Henrik, M. (2018). Electricity consumption clustering using smart meter data. Energies, 11(4), 859. Search in Google Scholar

Xu, J., & Yang, X. (2021). Direct effect and spillover effect of ict on electricity consumption in china: evidence from a spatial panel analysis. Mathematical Problems in Engineering. Search in Google Scholar

Yao, C. Z., Kuang, P. C., Lin, Q. W., & Sun, B. Y. (2017). A study of the transfer entropy networks on industrial electricity consumption. Entropy, 19(4), 159. Search in Google Scholar

Gu, Z. W., Li, P., Lang, X., Shen, X., Cao, M., & Yang, X. H. (2021). Hierarchical classification method of electricity consumption industries through tnpe and bayes: Measurement and Control, 54(3-4), 346-359. Search in Google Scholar

Jin, Tao, George, & Michailidis. (2019). A statistical framework for detecting electricity theft activities in smart grid distribution networks. IEEE Journal on Selected Areas in Communications, 38(1), 205-216. Search in Google Scholar

Shen, M., Lu, Y., Wei, K. H., & Cui, Q. (2020). Prediction of household electricity consumption and effectiveness of concerted intervention strategies based on occupant behaviour and personality traits. Renewable and Sustainable Energy Reviews, 127. Search in Google Scholar

Zhou, K., Yang, C., & Shen, J. (2017). Discovering residential electricity consumption patterns through smart-meter data mining: a case study from china. Utilities Policy, 44(FEB.), 73-84. Search in Google Scholar

eISSN:
2444-8656
Langue:
Anglais
Périodicité:
Volume Open
Sujets de la revue:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics