Probabilistic Static Voltage Stability of Power System with Integration of PV Generators using Monte Carlo Simulations: Probabilistic Static Voltage Stability of Power System

Awan Uji  Krismanto; Hafizhul Ayyasi  Khairullah; Irrine Budi  Sulistiawati; Abraham  Lomi; Dipu  Sarkar

doi:10.53560/PPASA(58-sp1)735

Authors

Awan Uji Krismanto Department of Electrical Engineering, National Institute of Technology Malang, Jl. Raya Karanglo, Km. 2, Malang 65143, Indonesia.
Hafizhul Ayyasi Khairullah Department of Electrical Engineering, National Institute of Technology Malang, Jl. Raya Karanglo, Km. 2, Malang 65143, Indonesia.
Irrine Budi Sulistiawati Department of Electrical Engineering, National Institute of Technology Malang, Jl. Raya Karanglo, Km. 2, Malang 65143, Indonesia.
Abraham Lomi Department of Electrical Engineering, National Institute of Technology Malang, Jl. Raya Karanglo, Km. 2, Malang 65143, Indonesia.
Dipu Sarkar National Institute of Technology, Chumukeidma, Dimapur, Nagaland 797103, India

DOI:

https://doi.org/10.53560/PPASA(58-sp1)735

Keywords:

Photovoltaic Generator, Probability Distribution, Renewable Energy, Solar Energy, Voltage Fluctuation, Voltage Profiles

Abstract

As a renewable source, the uncertainties and intermittencies of solar irradiance have become the main concern in developing and integrating such power generation into an electricity network. In power system operation, it is important to maintain a stable voltage profile under random power injection from renewable power generations. The effect of photovoltaic (PV) power plants on the static voltage stability of the interconnected power system is presented in this paper. The probabilistic study was conducted through Monte Carlo Simulation (MCS) to investigate the fluctuation of voltage profiles under uncertain power injection from PV power plants. The standard test system of IEEE 14 bus and practical test system of Lombok, West Nusa Tenggara electricity network are investigated. It was noticed that the installation of a photovoltaic power plant affected the voltage profiles. The fluctuated condition of power injection from PV power plant resulted in more fluctuation of voltage profiles as indicated by higher standard deviation values. Moreover, distributed location of the PV power plant also influenced the circumstances of voltage fluctuation, providing less fluctuated condition of voltage profiles. Eventually, it can be observed that the voltage fluctuation would influence the static voltage stability of the interconnected power system.

References

A.U. Krismanto and N.Mithulanthan. Probabilistic small signal stability analysis of autonomous wind-diesel microgrid. ISGT Asia Pacific 2017. Auckland, New Zealand, (2017). DOI: 10.1109/ ISGT-Asia.2017.8378359

Anindhita, I. Rahardo, I. Fitriana, R.E.P. Dewi, E. Siregar, N. Niode, Yudiartono, A. Sugiyono, L.O.M.A. Wahid, P.T. Wijaya, and A.K. Paminto. Outlook Energi Indonesia 2018 - Energi Berkelanjutan untuk Transportasi Darat [Indonesia Energy Outlook 2018 - Sustainable Energy for Land Transportation]. Pusat Pengkajian Industri Proses dan Energi (PPIPE), Badan Pengkajian dan Penerapan Teknologi (BPPT). Jakarta, Indonesia (2018) [in Bahasa Indonesia]

REN21, Renewables 2020 Global Status Report, (2018).

E. Yandri. The effect of Joule heating to thermal performance of hybrid PVT collector during electricity generation. Renewable Energy, 111: 344– 352 (2017). DOI: 10.1016/j.renene.2017.03.094

R. Shah., M. Nadarajah., R. Bansal., K. Lee, and A. Lomi. Influence of large-scale PV on voltage stability of sub-transmission system. International Journal on Electrical Engineering and Informatics 4(1): 148–161 (2012). DOI: 10.15676/ijeei.2012.4.1.12

N. Dhlamini, and S.P.D. Chowdhury. Solar photovoltaic generation and its integration impact on the existing power grid. IEEE PES/IAS Power Africa, (2018) p. 710–715. DOI: 10.1109/ PowerAfrica.2018.8521003

F.A. Khalil, M. Asif, S. Anwar, Sana ul Haq, and F. Illahi. Solar tracking techniques and implementation in photovoltaic power plants: A review. Proceedings of the Pakistan Academy of Sciences A. Physical and Computational Sciences 54 (3): 231–241 (2017)R. Bayindir., Ş. Demirbaş., E. Irmak., U. Cetinkaya.,

A. Ova, and M. Yeşil. Effects of renewable energy sources on the power system. IEEE International Power Electronics and Motion Control Conference (PEMC) (2016). p. 388–393. DOI: 10.1109/ EPEPEMC.2016.7752029

P. Kundur., N.J. Balu, and M.G. Lauby. Power System Stability and Control (Vol. 7). McGraw-hill, New York (1994).

D. Wang., X. Yuan., M. Zhao, and Y. Qian. Impact of large-scale photovoltaic generation integration structure on static voltage stability in China's Qinghai province network. The Journal of Engineering 2017(13): 671–675 (2017). DOI: 10.1049/joe.2017.0414.

E. Munkhchuluun, and L. G. Meegahapola. Impact of the solar photovoltaic (PV) generation on long-term voltage stability of a power network. Conference: 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 1–6. 2017. DOI: 10.1109/ISGT-Asia.2017.8378456.

W. Suampun. Voltage stability analysis of grid- connected photovoltaic power systems using CPFLOW. Procedia Computer Science, 86: 301– 304, 2016. DOI: 10.1016/j.procs.2016.05.082

A. U. Krismanto, N. Mithulananthan, and I. Kamwa, Oscillatory stability assessment of microgrid in autonomous operation with uncertainties. IET Renewable Power Generation, 12(4): 494–504, 2018. DOI: 10.1049/iet-rpg.2017.0579

R. Sridharan. Gaussian Mixture Models and the EM Algorithm, (Lecture Notes - MIT CSAIL). (2017). https://people.csail.mit.edu/rameshvs/content/ gmm-em.pdf (Accessed on 15 January 2021).

G. Stefopoulos., A.P. Meliopoulos, and G.J. Cokkinides. Advanced probabilistic power flow methodology. 15th Power Systems Computation Conference. (PSCC) 2005, (2005) p. 22–26.

A.U. Krismanto., N. Mithulananthan, and I. Kamwa. Oscillatory stability assessment of microgrid in autonomous operation with uncertainties. IET Renewable Power Generation, 12(4): 494–504. (2018). DOI: 10.1049/iet-rpg.2017.0579

S. Conti, and S. Raiti. Probabilistic load flow using Monte Carlo techniques for distribution networks with photovoltaic generators. Solar Energy 81(12): 1473–1481 (2007). DOI: 10.1016/j. solener.2007.02.007

R. Liang, and J. Liao. A fuzzy-optimization approach for generation scheduling with wind and

solar energy systems. IEEE Transactions on Power Systems 22(4): 1665–1674 (2007). DOI: 10.1109/PWRS.2007.907527

J. Park., W. Liang., J. Choi., A.A. El-Keib., M. Shahidehpour, and R. Billinton. A probabilistic reliability evaluation of a power system including Solar/Photovoltaic cell generator. IEEE Power & Energy Society General Meeting, 2009, pp. 1–6. DOI: 10.1109/PES.2009.5275722

Q. Linan., Z. Dawei., S. Tao., C. Ning, and D. Jie. Photovoltaic generation model for power system transient stability analysis. International Journal of Computer and Electrical Engineering 5(3): 289– 300 (2013). DOI: 10.7763/IJCEE.2013.V5.717

Probabilistic Static Voltage Stability of Power System with Integration of PV Generators using Monte Carlo Simulations