AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Home iEnergy Article
PDF (587.4 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Review | Open Access

A review on applications of holomorphic embedding methods

Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA
Show Author Information

Abstract

The holomorphic embedding method (HEM) stands as a mathematical technique renowned for its favorable convergence properties when resolving algebraic systems involving complex variables. The key idea behind the HEM is to convert the task of solving complex algebraic equations into a series expansion involving one or multiple embedded complex variables. This transformation empowers the utilization of complex analysis tools to tackle the original problem effectively. Since the 2010s, the HEM has been applied to steady-state and dynamic problems in power systems and has shown superior convergence and robustness compared to traditional numerical methods. This paper provides a comprehensive review on the diverse applications of the HEM and its variants reported by the literature in the past decade. The paper discusses both the strengths and limitations of these HEMs and provides guidelines for practical applications. It also outlines the challenges and potential directions for future research in this field.

References

[1]

Tinney, W., Hart, C. (1967). Power flow solution by Newton’s method. IEEE Transactions on Power Apparatus and Systems, PAS-86: 1449–1460.

[2]

Stott, B., Alsac, O. (1974). Fast decoupled load flow. IEEE Transactions on Power Apparatus and Systems, PAS-93: 859–869.

[3]

Ward, J. B., Hale, H. W. (1956). Digital computer solution of power-flow problems [includes discussion]. Transactions of the American Institute of Electrical Engineers Part III: Power Apparatus and Systems, 75: 398–404.

[4]

Ajjarapu, V., Christy, C. (1992). The continuation power flow: A tool for steady state voltage stability analysis. IEEE Transactions on Power Systems, 7: 416–423.

[5]

Wang, T., Chiang, H. D. (2020). On the holomorphic and conjugate properties for holomorphic embedding methods for solving power flow equations. IEEE Transactions on Power Systems, 35: 2506–2515.

[6]
Trias, A. (2012). The holomorphic embedding load flow method. In: Proceedings of the 2012 IEEE Power and Energy Society General Meeting, San Diego, CA, USA.
[7]

Rao, S., Feng, Y., Tylavsky, D. J., Subramanian, M. K. (2016). The holomorphic embedding method applied to the power-flow problem. IEEE Transactions on Power Systems, 31: 3816–3828.

[8]

Liu, C., Wang, B., Xu, X., Sun, K., Shi, D., Bak, C. L. (2017). A multi-dimensional holomorphic embedding method to solve AC power flows. IEEE Access, 5: 25270–25285.

[9]

Chiang, H. D., Wang, T., Sheng, H. (2018). A novel fast and flexible holomorphic embedding power flow method. IEEE Transactions on Power Systems, 33: 2551–2562.

[10]

Rao, S. D., Tylavsky, D. J., Feng, Y. (2017). Estimating the saddle-node bifurcation point of static power systems using the holomorphic embedding method. International Journal of Electrical Power & Energy Systems, 84: 1–12.

[11]

Liu, C., Wang, B., Hu, F., Sun, K., Bak, C. L. (2018). Online voltage stability assessment for load areas based on the holomorphic embedding method. IEEE Transactions on Power Systems, 33: 3720–3734.

[12]

Zhang, W., Wang, T., Chiang, H. D. (2022). A novel FFHE-inspired method for large power system static stability computation. IEEE Transactions on Power Systems, 37: 726–737.

[13]

Sun, Y., Ding, T., Qu, M., Wang, F., Shahidehpour, M. (2022). Interval total transfer capability for mesh HVDC systems based on sum of squares and multi-dimensional holomorphic embedding method. IEEE Transactions on Power Systems, 37: 4157–4167.

[14]

Yao, R., Qiu, F. (2020). Novel AC distribution factor for efficient outage analysis. IEEE Transactions on Power Systems, 35: 4960–4963.

[15]

Yao, R., Qiu, F., Sun, K. (2022). Contingency analysis based on partitioned and parallel holomorphic embedding. IEEE Transactions on Power Systems, 37: 565–575.

[16]
Rao, S., Tylavsky, D. (2016). Nonlinear network reduction for distribution networks using the holomorphic embedding method. In: Proceedings of the 2016 North American Power Symposium (NAPS), Denver, CO, USA.
[17]

Zhu, Y., Tylavsky, D., Rao, S. (2018). Nonlinear structure-preserving network reduction using holomorphic embedding. IEEE Transactions on Power Systems, 33: 1926–1935.

[18]

Liu, C., Qin, N., Sun, K., Bak, C. L. (2019). Remote voltage control using the holomorphic embedding load flow method. IEEE Transactions on Smart Grid, 10: 6308–6319.

[19]

Rao, B. V., Stefan, M., Schwalbe, R., Karl, R., Kupzog, F., Kozek, M. (2021). Stratified control applied to a three-phase unbalanced low voltage distribution grid in a local peer-to-peer energy community. Energies, 14: 3290.

[20]

Luo, Y., Liu, C. (2023). Area interchange control using the holomorphic embedding load flow method considering automatic generation control. Electric Power Systems Research, 225: 109721.

[21]

Rao, B., Kupzog, F., Kozek, M. (2019). Three-phase unbalanced optimal power flow using holomorphic embedding load flow method. Sustainability, 11: 1774.

[22]
Sayed, A. R., Zhang, X., Wang, G., Wang, C., Qiu, J. (2023). Optimal operable power flow: Sample-efficient holomorphic embedding-based reinforcement learning. IEEE Transactions on Power Systems, https://doi.org/10.1109/TPWRS.2023.3266773.
[23]

Yao, R., Sun, K., Shi, D., Zhang, X. (2019). Voltage stability analysis of power systems with induction motors based on holomorphic embedding. IEEE Transactions on Power Systems, 34: 1278–1288.

[24]

Yao, R., Liu, Y., Sun, K., Qiu, F., Wang, J. (2020). Efficient and robust dynamic simulation of power systems with holomorphic embedding. IEEE Transactions on Power Systems, 35: 938–949.

[25]
Subramanian, M. K. (2014). Application of holomorphic embedding to the power-flow problem. Master’s Thesis, Arizona State University, USA.
[26]
Remmert, R. (1991). Complex integral calculus. In: Theory of Complex Functions. New York: Springer.
[27]

Trias, A., Marin, J. L. (2016). The holomorphic embedding loadflow method for DC power systems and nonlinear DC circuits. IEEE Transactions on Circuits and Systems I: Regular Papers, 63: 322–333.

[28]
Cuyt, A., Petersen, V. B., Verdonk, B., Waadeland, H., Jones, W. B. (2008). Exponential integrals and related functions. In: Handbook of Continued Fractions for Special Functions. Dordrecht: Springer.
[29]
Baker, G., Graves-Morris, P. (1996). Padé Approximants. Cambridge: Cambridge University Press.
[30]

Stahl, H. (1989). On the convergence of generalized Padé approximants. Constructive Approximation, 5: 221–240.

[31]

Stahl, H. (1997). The convergence of padé approximants to functions with branch points. Journal of Approximation Theory, 91: 139–204.

[32]
Trias, A. (2015). Fundamentals of the holomorphic embedding load-flow method. arXiv preprint, arXiv: 1509.02421.
[33]

Wang, T., Chiang, H. D. (2021). Theoretical study of non-iterative holomorphic embedding methods for solving nonlinear power flow equations: Algebraic property. IEEE Transactions on Power Systems, 36: 2934–2945.

[34]

Singh, P., Tiwari, R. (2019). STATCOM model using holomorphic embedding. IEEE Access, 7: 33075–33086.

[35]
Zhang, T., Li, Z., Zheng, J. H., Wu, Q. H., Zhou, X. (2020). Power flow analysis of integrated gas and electricity systems using the fast and flexible holomorphic embedding method. In: Proceedings of the 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Canada.
[36]
Pan, S., Li, Z., Zheng, J. H., Wu, Q. H. (2020). On convergence performance and its common domain of the fast and flexible holomorphic embedding method for power flow analysis. In: Proceedings of the 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Canada.
[37]

Wang, B., Liu, C., Sun, K. (2018). Multi-stage holomorphic embedding method for calculating the power–voltage curve. IEEE Transactions on Power Systems, 33: 1127–1129.

[38]
Zhu, Y., Tylavsky, D. (2016). Bivariate holomorphic embedding applied to the power flow problem. In: Proceedings of the 2016 North American Power Symposium (NAPS), Denver, CO, USA.
[39]

Liu, C., Sun, K., Wang, B., Ju, W. (2018). Probabilistic power flow analysis using multidimensional holomorphic embedding and generalized cumulants. IEEE Transactions on Power Systems, 33: 7132–7142.

[40]

Sun, Y., Ding, T., Han, O., Liu, C., Li, F. (2023). Static voltage stability analysis based on multi-dimensional holomorphic embedding method. IEEE Transactions on Power Systems, 38: 3748–3759.

[41]

Sun, Y., Ding, T., Qu, M., Li, F., Shahidehpour, M. (2021). Tight semidefinite relaxation for interval power flow model based on multi-dimensional holomorphic embedding method. IEEE Transactions on Power Systems, 36: 2138–2148.

[42]

Sun, Y., Ding, T., Shahidehpour, M. (2023). A multi-variable analytical method for energy flow calculation in natural gas systems. IEEE Transactions on Power Systems, 38: 1767–1770.

[43]

Sun, Y., Ding, T., Xu, T., Mu, C., Siano, P., Catalao, J. P. S. (2022). Power flow analytical method for three-phase active distribution networks based on multi-dimensional holomorphic embedding method. IEEE Transactions on Circuits and Systems II: Express Briefs, 69: 5069–5073.

[44]

Lai, Q., Liu, C., Sun, K. (2022). Analytical static voltage stability boundary based on holomorphic embedding. International Journal of Electrical Power & Energy Systems, 134: 107386.

[45]

Yao, R., Zhao, D., Sakis Meliopoulos, A. P., Singh, C., Mitra, J., Qiu, F. (2022). Advanced extended-term simulation approach with flexible quasisteady-state and dynamic semi-analytical simulation engines. iEnergy, 1: 124–132.

[46]
Klump, R. P., Overbye, T. J. (2000). A new method for finding low-voltage power flow solutions. In: Proceedings of the 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134), Seattle, WA, USA.
[47]

Leonidopoulos, G. (1995). Approximate linear decoupled solution as the initial value of power system load flow. Electric Power Systems Research, 32: 161–163.

[48]
Baghsorkhi, S. S., Suetin, S. P. (2015). Embedding AC power flow with voltage control in the complex plane: The case of analytic continuation via Padé approximants. arXiv preprint, arXiv: 1504.03249.
[49]
Subramanian, M. K., Feng, Y., Tylavsky, D. (2013). PV bus modeling in a holomorphically embedded power-flow formulation. In: Proceedings of the 2013 North American Power Symposium (NAPS), Manhattan, KS, USA.
[50]
Baghsorkhi, S. S., Suetin, S. P. (2016). Embedding AC power flow in the complex plane Part I: Modelling and mathematical foundation. arXiv preprint, arXiv: 1609.01211.
[51]
Wallace, I., Roberts, D., Grothey, A., McKinnon, K. (2016). Alternative PV bus modelling with the holomorphic embedding load flow method. arXiv preprint, arXiv: 1607.00163.
[52]

Basiri-Kejani, M., Gholipour, E. (2017). Holomorphic embedding load-flow modeling of thyristor-based FACTS controllers. IEEE Transactions on Power Systems, 32: 4871–4879.

[53]

Singh, P., Senroy, N., Tiwari, R. (2021). Guaranteed convergence embedded system for SSSC and IPFC. IEEE Transactions on Power Systems, 36: 2725–2728.

[54]

Singh, P., Senroy, N. (2021). Steady-state models of STATCOM and UPFC using flexible holomorphic embedding. Electric Power Systems Research, 199: 107390.

[55]

Sur, U., Biswas, A., Bera, J. N., Sarkar, G. (2020). A modified holomorphic embedding method based hybrid AC-DC microgrid load flow. Electric Power Systems Research, 182: 106267.

[56]

Zhao, Y., Li, C., Ding, T., Hao, Z., Li, F. (2021). Holomorphic embedding power flow for AC/DC hybrid power systems using bauer’s ETA algorithm. IEEE Transactions on Power Systems, 36: 3595–3606.

[57]

Huang, Y., Ai, X., Fang, J., Yao, W., Wen, J. (2020). Holomorphic embedding approach for VSC-based AC/DC power flow. IET Generation, Transmission & Distribution, 14: 6239–6249.

[58]

Morgan, M. Y., Shaaban, M. F., Sindi, H. F., Zeineldin, H. H. (2022). A holomorphic embedding power flow algorithm for islanded hybrid AC/DC microgrids. IEEE Transactions on Smart Grid, 13: 1813–1825.

[59]

Huang, Y., Ai, X., Fang, J., Cui, S., Zhong, R., Yao, W., Wen, J. (2023). Holomorphic embedding power flow modeling of autonomous AC/DC hybrid microgrids. International Journal of Electrical Power & Energy Systems, 145: 108549.

[60]
Sun, L., Ju, Y., Yang, L., Ge, S., Fang, Q., Wang, J. (2018). Holomorphic embedding load flow modeling of the three-phase active distribution network. In: Proceedings of the 2018 International Conference on Power System Technology (POWERCON), Guangzhou, China.
[61]

Keihan Asl, D., Mohammadi, M., Reza Seifi, A. (2019). Holomorphic embedding load flow for unbalanced radial distribution networks with DFIG and tap-changer modelling. IET Generation, Transmission & Distribution, 13: 4263–4273.

[62]
Heidarifar, M., Andrianesis, P., Caramanis, M. (2019). Efficient load flow techniques based on holomorphic embedding for distribution networks. In: Proceedings of the 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA.
[63]

Heidarifar, M., Andrianesis, P., Caramanis, M. (2023). Holomorphic embedding load flow method in three-phase distribution networks with ZIP loads. IEEE Transactions on Power Systems, 38: 4605–4616.

[64]

Shamseldein, M. (2022). A fast holomorphic embedding power flow approach for meshed distribution networks. International Transactions on Electrical Energy Systems, 2022: 9561385.

[65]

Massrur, H. R., Niknam, T., Aghaei, J., Shafie-khah, M., Catalao, J. P. S. (2018). Fast decomposed energy flow in large-scale integrated electricity–gas–heat energy systems. IEEE Transactions on Sustainable Energy, 9: 1565–1577.

[66]

Massrur, H. R., Niknam, T., Fotuhi-Firuzabad, M. (2018). Investigation of carrier demand response uncertainty on energy flow of renewable-based integrated electricity–gas–heat systems. IEEE Transactions on Industrial Informatics, 14: 5133–5142.

[67]

Huang, Y., Ai, X., Fang, J., Cui, S., Zhong, R., Yao, W., Wen, J. (2022). Holomorphic embedding power flow algorithm for isolated AC microgrids with hierarchical control. IEEE Transactions on Smart Grid, 13: 1679–1690.

[68]
Sun, Y., Ding, T., Zhang, J., Shahidehpour, M., Jia, W., Xue, Y. (2023). An analytical steady heat flow calculation method for district heating networks. IEEE Transactions on Sustainable Energy: https://doi.org/10.1109/TSTE.2023.3328155.
[69]

Chiang, H. D., Flueck, A. J., Shah, K. S., Balu, N. (1995). CPFLOW: A practical tool for tracing power system steady-state stationary behavior due to load and generation variations. IEEE Transactions on Power Systems, 10: 623–634.

[70]
Rao, S., Tylavsky, D., Vittal, V., Yi, W., Shi, D., Wang, Z. (2018). Fast weak-bus and bifurcation point determination using holomorphic embedding method. In: Proceedings of the 2018 IEEE Power & Energy Society General Meeting (PESGM), Portland, OR, USA.
[71]
Trias, A. (2018). Sigma algebraic approximants as a diagnostic tool in power networks. US Patent, 9,563,722, 2017-2-7.
[72]
Lai, Q., Liu, C., Sun, K. (2020). A network decoupling method for voltage stability analysis based on holomorphic embedding. arXiv preprint, arXiv: 2003.12287.
[73]

Singh, P., Tiwari, R. (2020). Extended holomorphic embedded load-flow method and voltage stability assessment of power systems. Electric Power Systems Research, 185: 106381.

[74]

Lai, Q., Liu, C., Sun, K. (2021). Vulnerability assessment for voltage stability based on solvability regions of decoupled power flow equations. Applied Energy, 304: 117738.

[75]

Lai, Q., Liu, C., Sun, K. (2022). Formulation and visualization of bus voltage-var safety regions for a power system. IEEE Transactions on Power Systems, 37: 3153–3156.

[76]

Gao, H., Chen, J., Diao, R., Zhang, J. (2021). A HEM-based sensitivity analysis method for fast voltage stability assessment in distribution power network. IEEE Access, 9: 13344–13353.

[77]

Yao, R., Sun, K., Qiu, F. (2019). Vectorized efficient computation of padé approximation for semi-analytical simulation of large-scale power systems. IEEE Transactions on Power Systems, 34: 3957–3959.

[78]
Feng, Y., Tylavsky, D. (2013). A novel method to converge to the unstable equilibrium point for a two-bus system. In: Proceedings of the 2013 North American Power Symposium (NAPS), Manhattan, KS, USA.
[79]
Xu, X., Liu, C., Sun, K. (2018). A holomorphic embedding method to solve unstable equilibrium points of power systems. In: Proceedings of the 2018 IEEE Conference on Decision and Control (CDC), Miami Beach, FL, USA.
[80]

Li, S., Tylavsky, D., Shi, D., Wang, Z. (2021). Implications of Stahl’s theorems to holomorphic embedding Part I: Theoretical convergence. CSEE Journal of Power and Energy Systems, 7: 761–772.

[81]

Rao, S. D., Tylavsky, D. J. (2018). Theoretical convergence guarantees versus numerical convergence behavior of the holomorphically embedded power flow method. International Journal of Electrical Power & Energy Systems, 95: 166–176.

[82]

Dronamraju, A., Li, S., Li, Q., Li, Y., Tylavsky, D., Shi, D., Wang, D. (2021). Implications of stahl’s theorems to holomorphic embedding Part II: Numerical convergence. CSEE Journal of Power and Energy Systems, 7: 773–784.

[83]
Sauter, P. S., Braun, C. A., Kluwe, M., Hohmann, S. (2017). Comparison of the holomorphic embedding load flow method with established power flow algorithms and a new hybrid approach. In: Proceedings of the 2017 Ninth Annual IEEE Green Technologies Conference (GreenTech), Denver, CO, USA.
[84]

Liu, J., Yao, R., Qiu, F., Liu, Y., Sun, K. (2023). PowerSAS.m—An open-source power system simulation toolbox based on semi-analytical solution technologies. IEEE Open Access Journal of Power and Energy, 10: 222–232.

iEnergy
Pages 264-274
Cite this article:
Huang K, Sun K. A review on applications of holomorphic embedding methods. iEnergy, 2023, 2(4): 264-274. https://doi.org/10.23919/IEN.2023.0037

343

Views

16

Downloads

0

Crossref

0

Scopus

Altmetrics

Received: 18 September 2023
Revised: 11 November 2023
Accepted: 27 November 2023
Published: 19 December 2023
© The author(s) 2023.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Return