Abstract
Aiming at the poor real-time performance of single-channel grouping power consumption data acquisition, an intelligent data acquisition method based on symmetric mathematics is proposed. SM4, AES, DES, and RC6 are selected as the objects to design the top-level architecture of the symmetric key algorithm to ensure the integrity and confidentiality of the power consumption data of single channel grouping in the smart grid communication logic structure. Based on the microprocessor STM32F103RBT6, the power consumption data of single channel grouping collector is designed. The collector uses the data balance-based data acquisition routing mechanism to automatically adjust the sampling period, the adjustment factor, and the matching ratio of the reconstructed output of the single-channel packet data. Finally, the power consumption data of single channel grouping is completed. The experimental results show that the long-distance transmission time and important telemetry transmission time obtained by this method are 1.51 s and 1.47 s respectively, which are only about 50% of the standard requirements. The CPU load is 6.40%, which is only 23.7% of the standard CPU load demand, and the transmission failure rate and delay of power consumption data are relatively low.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Huang, Y., Zhan, J., Luo, C., Wang, L., Wang, N., Zheng, D., et al. (2019). An electricity consumption model for synthesizing scalable electricity load curves. Energy, 169, 674–683.
Cui, G. C., Liu, B., Luan, W. P., & Yu, Y. X. (2019). Estimation of target appliance electricity consumption using background filtering. IEEE Transactions on Smart Grid, 10, 5920–5929.
Guermandi, M., Cardu, R., Franchi, S. E., & Guerrieri, R. (2017). Active electrode IC for EEG and electrical impedance tomography with continuous monitoring of contact impedance. IEEE Transactions on Biomedical Circuits & Systems, 9, 21–33.
Guerrero, F. N., & Spinelli, E. M. (2017). A simple encoding method for sigma-delta ADC based biopotential acquisition systems. Journal of Medical Engineering & Technology, 41, 1–7.
Sole´-Torres, C., Puig-Bargue´s, J., Duran-Ros, M., Arbat, G., & Cartagena, F. R. D. (2019). Effect of underdrain design, media height and filtration velocity on the performance of microirrigation sand filters using reclaimed effluents. Biosystems Engineering, 187, 292–304.
Wang, K., & Gao, J. (2021). Abnormal behavior analysis of electricity consumption based on improved random forest with grey relation projection. Journal of Physics: Conference Series, 1754(1), 012027.
Wu, X., Jiao, D., Liang, K. X., & Han, X. (2019). A fast online load identification algorithm based on V-I characteristics of high-frequency data under user operational constraints. Energy, 188, 1–15.
Sean, W. Y., Chu, Y. Y., Mallu, L. L., Chen, J. G., & Liu, H. Y. (2020). Energy consumption analysis in wastewater treatment plants using simulation and SCADA system: Case study in northern Taiwan. Journal of Cleaner Production, 276(5), 124.
Pinto, T., Praa, I., Vale, Z., & Silva, J. (2020). Ensemble learning for electricity consumption forecasting in office buildings. Neurocomputing, 423, 747–755.
Wang, B., Yuan, Z. Y., Liu, X. X., Sun, Y. F., Zhang, B., & Wang, Z. H. (2021). Electricity price and habits: Which would affect household electricity consumption? Energy and Buildings, 240, 110888.
Wu, C. F., Huang, S. C., Chiou, C. C., Chang, T., & Chen, Y. C. (2021). The relationship between economic growth and electricity consumption: Bootstrap ARDL test with a fourier function and machine learning approach. Computational Economics, 7, 1–24.
Chen, Y. T., Sun, E. W., & Lin, Y. B. (2020). Machine learning with parallel neural networks for analyzing and forecasting electricity demand. Computational Economics, 56, 569–597.
Wang, B., & Wang, F. (2021). Research on intelligent lighting distributed control algorithm based on sensor network technology. Microprocessors and Microsystems, 81, 103729.
Lin, Z., Cheng, L., & Huang, G. (2020). Electricity consumption prediction based on LSTM with attention mechanism. IEEJ Transactions on Electrical and Electronic Engineering, 15(4), 556–562.
Wang, Z., Hong, T. Z., Li, H., & Piette, M. A. (2021). Predicting city-scale daily electricity consumption using data-driven models. Advances in Applied Energy, 2, 100025.
Grunewald, P., & Diakonova, M. (2020). Energy and enjoyment: The value of household electricity consumption. In Energy and behavior (pp. 263–281). Academic Press.
Delbourgo, D., & Gilmore, H. (2019). Computing L—invariants for the symmetric square of an elliptic curve. Experimental Mathematics, 30, 1–24.
Zhang, Q., & Hu, Y. (2019). Self-similar solutions to the spherically-symmetric euler equations with a two-constant equation of state. Indian Journal of Pure & Applied Mathematics, 50(1), 35–49.
Morikuni, K. (2019). Inner-iteration preconditioning with symmetric splitting matrices for symmetric singular linear systems. Transactions of the Japan Society for Industrial and Applied Mathematics, 29, 62–77.
Butorin, D. V., Filippenko, N. G., Bakanin, D. V., Bychkovsky, V. S., Larchenko, A. G., & Livshits, A. V. (2020). Mathematical modeling of electrothermal processes using the example of high-frequency welding of a batch of symmetric polymer workpieces. Journal of Physics Conference Series, 1614, 012052.
Tang, L., Zhou, S., Chen, J., et al. (2021). Metric dimension and metric independence number of incidence graphs of symmetric designs. Discrete Applied Mathematics, 291(4), 43–50.
Liu, Y., Yang, C., Sun, Q., et al. (2019). Enhanced embedding capacity for the SMSD-based data-hiding method. Signal Processing: Image Communication, 78, 216–222.
Song, J., Zhong, Q., Wang, W., et al. (2020). FPDP: Flexible privacy-preserving data publishing scheme for smart agriculture. IEEE Sensors Journal, 99, 1.
Mi, C., Wang, J., Mi, W., Huang, Y., Zhang, Z., Yang, Y., Jiang, J., & Octavian, P. (2019). Research on regional clustering and two-stage SVM method for container truck recognition. Discrete and Continuous Dynamical Systems Series S, 12(4–5), 1117–1133.
Pujals, E., Shub, M., & Yang, Y. (2020). Stable and non-symmetric pitchfork bifurcations. Science China Mathematics, 63(9), 1837–1852.
Yeliussizov, D. (2020). Positive specializations of symmetric Grothendieck polynomials. Advances in Mathematics, 363, 107000.
Zhang, W. (2020). Parameter adjustment strategy and experimental development of hydraulic system for wave energy power generation. Symmetry (Basel), 12(5), 711.
Xu, Y. Q., & Li, J. Z. (2019). Research of express scheduling system based on GIS. Automation & Instrumentation, 231, 32–35.
Zhu, J. X., Wang, X. Y., Chen, M. C., Wu, P., & Kim, M. J. (2019). Integration of BIM and GIS: IFC geometry transformation to shapefile using enhanced open-source approach. Automation in Construction, 106, 59.
Zhu, J., Wang, X., Wang, P., Wu, Z., & Kim, M. J. (2019). Integration of BIM and GIS: Geometry from IFC to shapefile using open-source tech-nology. Automation in Construction, 102, 105–119.
Daizadeh, I. (2021). Trademark and patent applications are structurally near-identical and cointegrated: Implications for studies in innovation. Iberoamerican Journal of Science Mea-surement and Communication, 1(2), 1–16.
Chen, Z.Q., Kumagai, T., & Wang, J. (2020). Heat kernel estimates and parabolic Harnack inequalities for symmetric Dirichlet forms. Advances in Mathematics, 374, 107269.
Cao, B., Fan, S. S., Zhao, J. W., Yang, P., Muhammad, K., & Tanveer, M. (2020). Quantum-enhanced multiobjective large-scale optimization via parallelism. Swarm and Evolutionary Computation, 57, 100697.
Cao, B., Wang, X. S., Zhang, W. Z., Song, H. B., & Lv, Z. H. (2020). A many-objective optimization model of industrial internet of things based on pri-vate blockchain. IEEE Network, 34(5), 78–83.
Daneshgar, A., & Taherkhani, A. (2019). A class of highly symmetric graphs, symmetric cylindrical constructions and their spectra. Discrete Mathematics, 342(1), 96–112.
Krishnaswamy, D., & Narayanasamy, A. (2019). On sums of range symmetric matrices with reference to indefinite inner product. Indian Journal of Pure and Applied Mathematics, 50(2), 499–510.
Xiong, Z. G., Tang, Z. W., Chen, X. E., Zhang, X. M., Zhang, K. B., & Ye, C. H. (2019). Research on image retrieval algorithm based on combination of color and shape features. Journal of Signal Processing Systems, 93(10), 139–146.
Ni, T. M., Xu, Q., Huang, Z. F., & Liang, H. G. (2020). A cost-effective TSV repair architecture for clustered faults in 3D IC. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. https://doi.org/10.1109/TCAD.2020.3025169
Wang, P., Chen, C. M., Kumari, S., & Shojafar, M. (2020). HDMA: Hybrid D2D message authentication scheme for 5G-enabled VANETs. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2020.3013928
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Sun, J. Intelligent acquisition method for power consumption data of single channel grouping based on symmetric mathematics. Wireless Netw 28, 2275–2287 (2022). https://doi.org/10.1007/s11276-021-02704-0
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DOI: https://doi.org/10.1007/s11276-021-02704-0