Many branches of Power Engineering have the same problems with signal processing. However they can be solved by a general approach. One of these problems is the complexity of signal description with the inertial change (without sharp peaks and dips), but the signal is a complex shape without symmetry and poorly responds to the cycling laws. Also offered, if it is necessary, to use the segmentation of the original signal with further Multiresolutional analysis. As a result, it is possible to make the selection with the most informative wavelet coefficients which can significantly reduce the quantity of the original data set with accuracy within acceptable limits.
Published in | American Journal of Environmental Protection (Volume 4, Issue 2) |
DOI | 10.11648/j.ajep.20150402.14 |
Page(s) | 95-100 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Multiresolutional Analysis, Wavelet Analysis, Description, Two-Peak Characteristics
[1] | А. Voloshko, Т. Lutchyn, “Principle of Determining Informative Wavelet Transformed Values in a Partial Restoration of Original Data Sample”, Registration, Storing and Data Process, 14:4 (2012), 33-40. – (in Rus.). |
[2] | W. Lian, A. Mao, L. Zhang, “A Method for Cascading Failure Simulation based on Static Security Analysis”, 10.1109/APPEEC.2009.4918053. |
[3] | A. Vahidnia, A. Dastfan, M. Banejad, “Determination of Harmonic Load Characteristics in Distribution Networks of Cities” Power Engineering, Energy and Electrical Drives, 2009. POWERENG '09. Intern. Conf., (2009), 442-446. |
[4] | Z. Zakaria, K. L. Lo, “Two-stage Fuzzy Clustering Approach for Load Profiling”, Universities Power Engineering Conference (UPEC), 2009 Proc. of the 44thIntern., (2009), 1-5. |
[5] | X. Ge, L. Zhang, Ya. Yang, “Multi-objective Hydro Optimal Scheduling with Flow Time”, 10.1109/PowerCon.2012.6401259. |
[6] | L. Kipinski, R. Konig, C. Sieluzycki, “Application of modern tests for stationarity to singletrial MEG data. Transferring powerful statistical tools from econometrics to neuroscience”, Biological Cybernetics, 105 (2011), 183–195. |
[7] | Yu. Yagi, Yu. Fukahata, “Introduction of uncertainty of Green’s function into waveform inversion for seismic source processes”, Geophysical Journal International, 186 (2011), 711–720. |
[8] | A. C. Iliopoulos, G. P. Pavlos, “Global Low Dimensional Seismic Chaos in the Hellenic Region”, International Journal of Bifurcation and Chaos, 20:7 (2010), 2071-2095. |
[9] | C. L. Bain, J. de Paz, J. Kramer, “Detecting the ITCZ in Instantaneous Satellite Data using Spatiotemporal Statistical Modeling: ITCZ Climatology in the East Pacific”, American Meteorological Society, 24 (2011), 216-230. |
[10] | T. Kozu, K. Masuzawa, T. Shimomai, “Estimation of No* for the Two-Scale Gamma Raindrop Size Distribution Model and Its Statistical Properties at Several Locations in Asia”, Journal of Applied Metrology and Climatology, 49 (2010), 676–686. |
[11] | F. Qi, X. Liu, Yi. Ma, “Synthesis of neural tree models by improved breeder genetic programming”, Neural Computing & Applications, 21 (2012), 515–521. |
[12] | M. M. Katsova, I. M. Livshits, J. Sykora, “The Rotation of the Sun as a Star from the Green-Line Emission of the Entire Corona”, Astronomy Reports 86:4 (2009), 343-354. |
[13] | Th. Candela, F. ois Renard, M. Bouchon, “Characterization of Fault Roughness at Various Scales: Implications of Three-Dimensional High Resolution Topography Measurements”, Pure & Applied Geophysic, 166 (2009), 1817–1851. |
[14] | R. Liu, M. Chen, H.-X. Wang, “Study on Grouping Control Strategy of AGC Units”, 10.1109/ISGT-Asia.2012.6303348. |
[15] | J. A. Jardini, C. M. V. Tahan, E. L. Ferrari, S. U. Ahn, “Selection of Distribution Transformer Based on Economic Criteria”, Electricity Distribution. Part 1: Contributions. CIRED. 14th Intern. Conf. and Exhibition, 6 (1997), 7. |
[16] | M. H. Shariatkhah, M. R. Haghifam, “Determining of Annual Distribution Feeder Configuration Using Load Curves Clustering”, Electrical Power Distribution Networks (EPDC), 2011 16th Conf., (2011) |
[17] | Ch. Preet, G. Yadwinder, B. Kanwardeep, “Incentive Based Demand Response Program: an Effective Way to Tackle Peaking Electricity Crisis”, 10.1109/CCECE.2012.6334813. |
[18] | G. I. Rhodes, “A Method of Studying Power Costs with Reference to the Load Curve and Overload Economies” American Institute of Electrical Engineers, (1912), 81-100. |
[19] | S. Kahrobaee, R. A. Rajabzadeh, L-K. Soh, “A Multiagent Modeling and Investigation of Smart Homes With Power Generation, Storage, and Trading Features”, Smart Grid, IEEE Transactions, 4:2 (2012), 659-668. |
[20] | S. V. Verdu, M. O. Garcia, F. J. G. Franco, “Characterization and Identification of Electrical Customers Through the Use of Self-Organizing Maps and Daily Load Parameters”, Power Systems Conf. and Exposition, 2004. IEEE PES, 2 (2004), 899-906. |
[21] | J. A. Jardini, C. M. V. Tahan, M. R. Gouvea, “Daily Load Profiles for Residential, Commercial and Industrial Low Voltage Consumers”, Power Delivery, IEEE Transactions, 15:1 (2000), 375-380. |
[22] | A. L. Shenkman, “Energy Loss Computation by Using Statistical Techniques”, IEEE Transactions on Power Delivery, 5:1 (1990), 254-258. |
[23] | P. Kadar, “Understanding customer behavior”, 10.1109/TDC-LA.2008.4641800. |
[24] | Sh. Yang, Yi. Zhang, “Short-term Load Forecast Based on Decomposition of Daily Load Curve”, 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE) 3 (2010), 65-68. |
[25] | Yu. Sabri, N. Hariyanto, F. Fitriana, “Spatial Short-Term Load Forecasting using Grey Dynamic Model Specific in Tropical Area”, 10.1109/ICEEI.2011.6021776. |
[26] | Q. Ding, J. Lu, H. Liao, “A Practical Super Short Term Load Forecast Method and Its Implementations”, Power Systems Conference and Exposition, 2004. IEEE PES, 1 (2004), 483-486. |
[27] | M. B. Tasre, V. N. Ghate, P. P. Bedekar, “Comparative Analysis of Hourly Load Forecast for a Small Load Area”, 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET) (2012), 80-85. |
[28] | F. X. Xie, M. Huang, W. G. Zhang, “Research on Electric Vehicle Charging Station Load Forecasting”, The International Conference on Advanced Power System Automation and Protection 2011 IEEE (2011), 2055-2060. |
[29] | R. Afkhami, F. M. Yazdi, “Application of Neural Networks for Short-Term Load Forecasting”, 10.1109/POWERI.2006.1632536. |
[30] | M. Lopez, S. Valero, C. Senabre, “A SOM Neural Network Approach to Load Forecasting. Meteorological and Time Frame Influence”, 10.1109/PowerEng.2011.6036553. |
[31] | J. Nazarko, A. Jurczuk, W. Zalewski, “ARIMA Models in Load Modelling with Clustering Approach”, 10.1109/PTC.2005.4524719. |
[32] | P. T. T. Binh, N. T. Hung, P. Q. Dung, “Load Forecasting Based on Wavelet Transform and Fuzzy Logic”, 10.1109/PowerCon.2012.6401281. |
[33] | I. Erkmen, A. Ozdogan, “Short Term Load Forecasting Using Genetically Optimized Neural network Cascaded with a Modified Kohonen Clustering Process”, Proceedings of the 12th IEEE International Symposium on Intelligent Control (1997), 107-112. |
[34] | D. Srinivasan, A.C. Liew, C.S. Chang, “Forecasting daily load curves using a hybrid fuzzyneutral approach”, IEE Processing-Generation, Transmission, Distribution, 141:6 (1994), 561-567. |
[35] | D. M. FalcZio, H.O. Henriques, “Load Estimation in Radar Distribution Systems Using Networks and Fuzzy Set Techniques”, Power Engineering Society Summer Meeting, 2 (2001), 1002-1006. |
[36] | M. Elsayed, “An overview of wavelet analysis and its application to ocean wind waves”, Journal of Coastal Research, 26:3 (2010), 535–540. |
[37] | G. M. Menanno, A. Mazzotti, “Deconvolution of multicomponent seismic data by means of quaternions: Theory and preliminary results”, Geophysical Prospecting, 60 (2012), 217–238. |
[38] | M. R. Homaeinezhad, M. Aghaee, H. N. Toosi, “Application of the Discrete Wavelet Transform for the Robust Detection of the Impulsive Incidences: Application to Arterial Blood Pressure Characteristic Events Detection-Delineation”, International Journal of Wavelets, Multiresolution and Information Processing, 9:5 (2011), 813–842. |
[39] | G. Hall, S. Woodborne, M. Pienaar, “Rainfall control of the δ13C ratios of Mimusops caffra from KwaZulu-Natal, South Africa”, The Holocene, 19:2 (2009), 251–260. |
[40] | Kh. Mistry, R. Roy, “Enhancement of Voltage Stability Index of Distribution System by Network Reconfiguration Including Static Load Model and Daily Load Curve”, Innovative Smart Grid Technologies - India (ISGT India), 2011 IEEE PES21 (2011), 65-68. |
[41] | D. Raisz, A. M. Dan, “Ripple Control as a Possible Tool for Daily Load Balancing in an Open Electricity Market Environment”, 10.1109/PTC.2005.4524451. |
[42] | I. М. Dremin, О. V. Ivanov, V. А. Nechytailo, “Wavelets and its Usage”, SFS, 171:5 (2001), 465–501. – (in Rus.). |
[43] | А. Voloshko, Т. Lutchyn, “Analysis of the Efficiency of Measures Compress of Schedules of Electrical Loads Аналіз ефективності міри стиснення графіків електричних навантажень”, Vinnitsa NTU, 16:4 (2011), 209-214. – (in Ukr.). |
APA Style
Tetiana Lutchyn. (2015). Description of Two-Peak Characteristics in Power Engineering. American Journal of Environmental Protection, 4(2), 95-100. https://doi.org/10.11648/j.ajep.20150402.14
ACS Style
Tetiana Lutchyn. Description of Two-Peak Characteristics in Power Engineering. Am. J. Environ. Prot. 2015, 4(2), 95-100. doi: 10.11648/j.ajep.20150402.14
AMA Style
Tetiana Lutchyn. Description of Two-Peak Characteristics in Power Engineering. Am J Environ Prot. 2015;4(2):95-100. doi: 10.11648/j.ajep.20150402.14
@article{10.11648/j.ajep.20150402.14, author = {Tetiana Lutchyn}, title = {Description of Two-Peak Characteristics in Power Engineering}, journal = {American Journal of Environmental Protection}, volume = {4}, number = {2}, pages = {95-100}, doi = {10.11648/j.ajep.20150402.14}, url = {https://doi.org/10.11648/j.ajep.20150402.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajep.20150402.14}, abstract = {Many branches of Power Engineering have the same problems with signal processing. However they can be solved by a general approach. One of these problems is the complexity of signal description with the inertial change (without sharp peaks and dips), but the signal is a complex shape without symmetry and poorly responds to the cycling laws. Also offered, if it is necessary, to use the segmentation of the original signal with further Multiresolutional analysis. As a result, it is possible to make the selection with the most informative wavelet coefficients which can significantly reduce the quantity of the original data set with accuracy within acceptable limits.}, year = {2015} }
TY - JOUR T1 - Description of Two-Peak Characteristics in Power Engineering AU - Tetiana Lutchyn Y1 - 2015/03/03 PY - 2015 N1 - https://doi.org/10.11648/j.ajep.20150402.14 DO - 10.11648/j.ajep.20150402.14 T2 - American Journal of Environmental Protection JF - American Journal of Environmental Protection JO - American Journal of Environmental Protection SP - 95 EP - 100 PB - Science Publishing Group SN - 2328-5699 UR - https://doi.org/10.11648/j.ajep.20150402.14 AB - Many branches of Power Engineering have the same problems with signal processing. However they can be solved by a general approach. One of these problems is the complexity of signal description with the inertial change (without sharp peaks and dips), but the signal is a complex shape without symmetry and poorly responds to the cycling laws. Also offered, if it is necessary, to use the segmentation of the original signal with further Multiresolutional analysis. As a result, it is possible to make the selection with the most informative wavelet coefficients which can significantly reduce the quantity of the original data set with accuracy within acceptable limits. VL - 4 IS - 2 ER -