The identification of harmonic generating loads and the assignation of responsibility for harmonic pollution is an important first step for harmonic control in modern power systems. In this paper, a previously introduced power multivector is examined as a possible tool for the identification of such loads. This representation of power is based on the mathematical framework of Geometric Algebra (GA). Components of the power multivector derived at the point of connection of a load are grouped into a single quantity, which is a bivector in GA and is characterized by a magnitude, direction and sense. The magnitude of this bivector can serve as an indicator of the distortion at the terminals of the load. Furthermore, in contrast to indices based solely on magnitude, such as components derived from any apparent power equation, the proposed bivectorial representation can differentiate between loads that enhance distortion and those with a mitigating effect. Its conservative nature permits an association between the distortion at specific load terminals and the common point of connection. When several loads connected along a distribution line are considered, then an evaluation of the impact of each one of these loads on the distortion at a specific point is possible. Simulation results confirm that information included in the proposed bivector can provide helpful guidance when quantities derived from apparent power equations deliver ambiguous results.
Citation: Anthoula Menti, Dimitrios Barkas, Pavlos Pachos, Constantinos S. Psomopoulos. Contribution of a power multivector to distorting load identification[J]. AIMS Energy, 2023, 11(2): 271-292. doi: 10.3934/energy.2023015
The identification of harmonic generating loads and the assignation of responsibility for harmonic pollution is an important first step for harmonic control in modern power systems. In this paper, a previously introduced power multivector is examined as a possible tool for the identification of such loads. This representation of power is based on the mathematical framework of Geometric Algebra (GA). Components of the power multivector derived at the point of connection of a load are grouped into a single quantity, which is a bivector in GA and is characterized by a magnitude, direction and sense. The magnitude of this bivector can serve as an indicator of the distortion at the terminals of the load. Furthermore, in contrast to indices based solely on magnitude, such as components derived from any apparent power equation, the proposed bivectorial representation can differentiate between loads that enhance distortion and those with a mitigating effect. Its conservative nature permits an association between the distortion at specific load terminals and the common point of connection. When several loads connected along a distribution line are considered, then an evaluation of the impact of each one of these loads on the distortion at a specific point is possible. Simulation results confirm that information included in the proposed bivector can provide helpful guidance when quantities derived from apparent power equations deliver ambiguous results.
[1] | Das SR, Mishra DP, Ray PK, et al. (2021) Power quality improvement using fuzzy logic-based compensation in a hybrid power system, Int J Power Electron Drive Syst 12: 576–584. https://doi.org/10.11591/ijpeds.v12.i1.pp576-584 doi: 10.11591/ijpeds.v12.i1.pp576-584 |
[2] | Das SR, Mishra AK, Ray PK, et al. (2022) Application of artificial intelligent techniques for power quality improvement in hybrid microgrid system. Electronics 11: 3826: 1–19. https://doi.org/10.3390/electronics11223826 doi: 10.3390/electronics11223826 |
[3] | Das B, Panigrahi PK, Das SR, et al. (2021) Power quality improvement in a photovoltaic based microgrid integrated network using multilevel inverter. Int J Emerg Electr Power Syst 23: 197–209. https://doi.org/10.1515/ijeeps-2021-0040 doi: 10.1515/ijeeps-2021-0040 |
[4] | Sinvula R, Abo-Al-Ez KM, Kahn MT (2019) Harmonic source detection methods: A systematic literature review. IEEE Access 7: 74283–74299. https://doi.org/10.1109/ACCESS.2019.2921149 doi: 10.1109/ACCESS.2019.2921149 |
[5] | Saxena D, Bhaumik S, Singh SN (2014) Identification of multiple harmonic sources in power system using optimally placed voltage measurement devices. IEEE Trans Ind Electron 61: 2483–2492. https://doi.org/10.1109/TIE.2013.2270218 doi: 10.1109/TIE.2013.2270218 |
[6] | Carta D, Muscas C, Pegoraro PA, et al. (2019) Identification and estimation of harmonic sources based on compressive sensing. IEEE Trans Instrum Meas 68: 95–104. https://doi.org/10.1109/TIM.2018.2838738 doi: 10.1109/TIM.2018.2838738 |
[7] | Li C, Xu W, Tayjasanant T (2004) A "critical impedance"—based method for identifying harmonic sources. IEEE Trans Power Deliv 19: 671–678. https://doi.org/10.1109/TPWRD.2004.825302 doi: 10.1109/TPWRD.2004.825302 |
[8] | Stevanović D, Petković P (2015) A single-point method for identification sources of harmonic pollution applicable to standard power meters. Electr Eng 97: 165–174. https://doi.org/10.1007/s00202-014-0324-z doi: 10.1007/s00202-014-0324-z |
[9] | Li C-S, Bai Z-X, Xiao X-Y, et al. (2016) Research of harmonic distortion power for harmonic source detection. International Conference on Harmonics and Quality of Power. IEEE, Belo Horizonte, Brazil, 1–4. https://doi.org/10.1109/ICHQP.2016.7783437 |
[10] | Anu G, Fernandez FM (2020) Identification of harmonic injection and distortion power at customer location. 19th International Conference on Harmonics and Quality of Power (ICHQP), Dubai, United Arab Emirates, 1–5. https://doi.org/10.1109/ICHQP46026.2020.9177869 |
[11] | Cataliotti A, Cosentino V, Nuccio S (2008) Comparison of nonactive powers for the detection of dominant harmonic sources in power systems. IEEE Trans Instrum Meas 57: 1554–1561. https://doi.org/10.1109/TIM.2008.925338 doi: 10.1109/TIM.2008.925338 |
[12] | Xu W, Liu X, Liu Y (2003) An investigation on the validity of power direction method for harmonic source determination. IEEE Trans Power Deliv 18: 214–219. https://doi.org/10.1109/TPWRD.2002.803842 doi: 10.1109/TPWRD.2002.803842 |
[13] | IEEE Std 1459-2010: IEEE Standard definitions for the measurement of electric power quantities under sinusoidal, nonsinusoidal, balanced, or unbalanced conditions, 2010. |
[14] | Menti A, Zacharias T, Milias-Argitis J (2007) Geometric algebra: a powerful tool for representing power under nonsinusoidal conditions. IEEE Trans Circuits Syst I, Fundam Theory Appl 54: 601–609. https://doi.org/10.1109/TCSI.2006.887608 doi: 10.1109/TCSI.2006.887608 |
[15] | Menti A, Zacharias Th, Milias-Argitis J (2010) Power components under nonsinusoidal conditions using a power multivector. Proc 10th Conference-Seminar International School on Nonsinusoidal Currents and Compensation (ISNCC). Lagow, Poland, 174–179. https://doi.org/10.1109/ISNCC.2010.5524495 |
[16] | Doran C, Lasenby A (2003) Geometric Algebra for Physicists. Cambridge University Press. https://doi.org/10.1017/CBO9780511807497 |
[17] | Bollen M, Olofsson M, Larsson A, et al. (2014) Standards for supraharmonics (2 to 150 kHz). IEEE Electromag Compatibil Mag 3: 114–119. https://doi.org/10.1109/MEMC.2014.6798813 doi: 10.1109/MEMC.2014.6798813 |
[18] | Barkas D, Ioannidis G, Kaminaris S, et al. (2022) Design of a supraharmonic monitoring system based on an FPGA device. Sensors 22: 1–20. https://doi.org/10.3390/s22052027 doi: 10.3390/s22052027 |
[19] | Menti A, Barkas D, Kaminaris S, et al. (2012) Supraharmonic emission from a three-phase PV system connected to the LV grid. Energy Rep 7: 527–542. https://doi.org/10.1016/j.egyr.2021.07.100 doi: 10.1016/j.egyr.2021.07.100 |