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  • 1 AL-Hikma University, Iraq
  • | 2 University of Nairobi, Kenya
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Abstract

The use of energy in the world today is increasing with increase in population. The cost and availability of energy significantly impacts our quality of life, the health of national economies and the stability of our environment. The rapid depletion of fossil fuel resources on a worldwide basis has necessitated an urgent search for alternative energy sources to cater to the present day demands. In recent years there has been a significant global commitment to develop clean and alternative sources of energy such as solar and wind. Wind energy technology has been the fastest growing energy source because it is fairly distributed around the world and readily available for use. However, more penetration of wind energy into existing power networks has some impacts on the stability of the power system. Therefore, this paper studies and analyzes the stability of a power system with increasing wind penetration. The paper presents some analyses of a power system and the dynamic behavior which identify the issues that limit the large-scale integration of wind generators in a power system.

Abstract

The use of energy in the world today is increasing with increase in population. The cost and availability of energy significantly impacts our quality of life, the health of national economies and the stability of our environment. The rapid depletion of fossil fuel resources on a worldwide basis has necessitated an urgent search for alternative energy sources to cater to the present day demands. In recent years there has been a significant global commitment to develop clean and alternative sources of energy such as solar and wind. Wind energy technology has been the fastest growing energy source because it is fairly distributed around the world and readily available for use. However, more penetration of wind energy into existing power networks has some impacts on the stability of the power system. Therefore, this paper studies and analyzes the stability of a power system with increasing wind penetration. The paper presents some analyses of a power system and the dynamic behavior which identify the issues that limit the large-scale integration of wind generators in a power system.

1 Introduction

Wind energy is one of the major sources of renewable energy with a remarkable contribution to the installed capacity of electrical power systems. Wind power has been used in ancient times for applications such as: pumping water, grinding mills and in propelling boats. Its contribution in the electricity supply began in the mid 1980s and is now firmly established as one of the major technologies of electricity generation in the world. It is one of the fastest growing electricity generating technologies in the world and features in both developed and developing countries.

Rapid expansion of wind power has been driven by a combination of its environmental benefits, various state and federal policies and incentives, and improving cost-competitiveness with other generating technologies.

The wind turbine generators in a wind farm are distributed within the farm, but the total output of the farm normally connects to the bulk power system at a single substation, in a fashion similar to conventional central-station generation. Integration of large quantities of wind power has, however, presented some challenges such as absorption of reactive power from the grid during faults, which affects system stability in weak power grids.

Power generation using wind differs in several respects from conventional sources of energy such as hydro and thermal, the major difference being that wind generators are usually based on induction generator technologies instead of the conventional synchronous generators. The induction generators are known to consume reactive power (like in induction motors) during system contingency, which in turn affect the stability of a power system.

The issue of the study dependent on the stability in a power system is during and after a fault is introduced to a system. Besides, if and just if the fault does not achieve any supportable change in power the machine must return to its unique state. In the event that imbalanced interest makes change in burden or system/generation condition, new working state is required. In this way, it very well may be said that in all matters inter-connected synchronous machines should maintain synchronism, for example they need to work at the same velocity in parallel. The system unsettling influence makes transients of oscillatory nature, however, on the off chance that nature of system is stable, these motions will be soak to new stable condition. Some related researches can be found in literature [1–6].

2 Methodology

2.1 Power system modeling using MATLAB Simulink

A micro-grid is modeled by connecting distributed generators near the load together with main grid as shown in Fig. 1.

Figure 1.
Figure 1.

Micro-grid system

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

Generator DG3 is introduced and integrated into the micro-grid. The generator DG3 represents a wind farm. The proposed wind farm is aggregated to an equivalent generator producing 300 MW. The wind power generator is modeled using MATLAB Simulink and integrated to the micro-grid.

2.2 Excitation control system

The automatic voltage regulator (AVR) and the power system stabilizer comprise the excitation control system. They are modeled and included in the system. Further simulations were carried out so as to ascertain their effect.

2.3 Simulation block diagrams

The load frequency control (LFC) model of an isolated power system is modeled as shown in Fig. 2.

Figure 2.
Figure 2.

Model of load frequency control

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

Figure 3 shows generator diagram with AVR.

Figure 3.
Figure 3.

Generator block diagram with AVR

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

Figure 4 shows generator diagram with AVR and feedback stabilizer.

Figure 4.
Figure 4.

Generator block diagram with AVR and rate feedback stabilizer

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

An assumption is made that wind speed is constant, all the wind turbines are exposed to the same wind speed and turbulence level. These assumptions are made so that the wind turbines could be considered to produce their maximum rated power. A short circuit fault is introduced on the bus connecting the micro-grid to the main grid. It is introduced after 1 s and cleared after 1.01 s by tripping the line. The behavior of the generators is observed and analyzed after the fault.

3 Simulation results

The simulations are carried out with and without the wind farm for the different models. The LFC of the isolated power system is simulated. The steady state response of LFC model with and without the wind farm is shown in Fig. 5.

Figure 5.
Figure 5.

Steady state response of LFC model

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

Figure 6 shows the transient response of the power system with AVR only.

Figure 6.
Figure 6.

Transient response with AVR only

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

Figure 7 shows transient response of the power system with AVR and rate feedback stabilizer.

Figure 7.
Figure 7.

Transient response with AVR and rate feedback stabilizer

Citation: International Review of Applied Sciences and Engineering IRASE 11, 1; 10.1556/1848.2020.00001

From the results it can be seen that with the inclusion of wind power, the terminal voltage takes a longer time to settle after the fault. Also, the frequency deviation takes a longer time to settle when the wind power is included. It is also noted that the damping is better when wind power is not included.

4 Conclusion and discussion

In this paper, stability of a power system was analyzed. The performance of the system without wind power was studied first and then was compared with the case when wind power is present. It was observed after considering the settling time of different parameters after a system fault that the operation of the system can be enhanced with inclusion of the excitation controllers in the model. This inclusion of the excitation control system is necessary when considering integrating this large wind farm into the system.

References

  • [1]

    J. Slootweg and W. Kling, “Modelling and analysing impacts of wind power on transient stability of power systems,” Wind Eng., vol. 26, no. 1, pp. 320, 2002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [2]

    R. Melício, V. Mendes, and J. Catalão, “Computer simulation of wind power systems: power electronics and transient stability analysis,” in Int. Conf. Power Sys. Trans., Kyoto, Japan. 2009.

    • Search Google Scholar
    • Export Citation
  • [3]

    B. Sun, H. Zhengyou, Y. Jia, and K. Liao, “Small-signal stability analysis of wind Power system based on DFIG,” Energy Power Eng., vol. 5, pp. 418422, 2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [4]

    M. Deshmukh and C. Moorthy, “Review on stability analysis of grid connected wind power generating system,” Int. J. Electr. Electron. Eng. Res., vol. 3, no. 1, pp. 133, 2013.

    • Search Google Scholar
    • Export Citation
  • [5]

    H. Rui, H. Weihao, and C. Zhe, “Review of power system stability with high wind power penetration,” Proc. 41th Annu. Conf. IEEE Indus. Electron. Soc., Yokohama, Japan, IEEE. 2015.

    • Search Google Scholar
    • Export Citation
  • [6]

    F. Islam and A. Lallu, “Impact of wind generators in power system stability.” WSEAS Trans. Power Syst., vol. 13, pp. 235248, 2018.

    • Search Google Scholar
    • Export Citation
  • [1]

    J. Slootweg and W. Kling, “Modelling and analysing impacts of wind power on transient stability of power systems,” Wind Eng., vol. 26, no. 1, pp. 320, 2002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [2]

    R. Melício, V. Mendes, and J. Catalão, “Computer simulation of wind power systems: power electronics and transient stability analysis,” in Int. Conf. Power Sys. Trans., Kyoto, Japan. 2009.

    • Search Google Scholar
    • Export Citation
  • [3]

    B. Sun, H. Zhengyou, Y. Jia, and K. Liao, “Small-signal stability analysis of wind Power system based on DFIG,” Energy Power Eng., vol. 5, pp. 418422, 2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [4]

    M. Deshmukh and C. Moorthy, “Review on stability analysis of grid connected wind power generating system,” Int. J. Electr. Electron. Eng. Res., vol. 3, no. 1, pp. 133, 2013.

    • Search Google Scholar
    • Export Citation
  • [5]

    H. Rui, H. Weihao, and C. Zhe, “Review of power system stability with high wind power penetration,” Proc. 41th Annu. Conf. IEEE Indus. Electron. Soc., Yokohama, Japan, IEEE. 2015.

    • Search Google Scholar
    • Export Citation
  • [6]

    F. Islam and A. Lallu, “Impact of wind generators in power system stability.” WSEAS Trans. Power Syst., vol. 13, pp. 235248, 2018.

    • Search Google Scholar
    • Export Citation
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  • M. N. Ahmad, Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Malaysia
  • M. Bakirov, Center for Materials and Lifetime Management Ltd., Moscow, Russia
  • N. Balc, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • U. Berardi, Ryerson University, Toronto, Canada
  • I. Bodnár, University of Debrecen, Debrecen, Hungary
  • S. Bodzás, University of Debrecen, Debrecen, Hungary
  • F. Botsali, Selçuk University, Konya, Turkey
  • S. Brunner, Empa - Swiss Federal Laboratories for Materials Science and Technology
  • I. Budai, University of Debrecen, Debrecen, Hungary
  • C. Bungau, University of Oradea, Oradea, Romania
  • M. De Carli, University of Padua, Padua, Italy
  • R. Cerny, Czech Technical University in Prague, Czech Republic
  • Gy. Csomós, University of Debrecen, Debrecen, Hungary
  • T. Csoknyai, Budapest University of Technology and Economics, Budapest, Hungary
  • G. Eugen, University of Oradea, Oradea, Romania
  • J. Finta, University of Pécs, Pécs, Hungary
  • A. Gacsadi, University of Oradea, Oradea, Romania
  • E. A. Grulke, University of Kentucky, Lexington, United States
  • J. Grum, University of Ljubljana, Ljubljana, Slovenia
  • G. Husi, University of Debrecen, Debrecen, Hungary
  • G. A. Husseini, American University of Sharjah, Sharjah, United Arab Emirates
  • N. Ivanov, Peter the Great St.Petersburg Polytechnic University, St. Petersburg, Russia
  • A. Járai, Eötvös Loránd University, Budapest, Hungary
  • G. Jóhannesson, The National Energy Authority of Iceland, Reykjavik, Iceland
  • L. Kajtár, Budapest University of Technology and Economics, Budapest, Hungary
  • F. Kalmár, University of Debrecen, Debrecen, Hungary
  • T. Kalmár, University of Debrecen, Debrecen, Hungary
  • M. Kalousek, Brno University of Technology, Brno, Czech Republik
  • J. Koci, Czech Technical University in Prague, Prague, Czech Republic
  • V. Koci, Czech Technical University in Prague, Prague, Czech Republic
  • I. Kocsis, University of Debrecen, Debrecen, Hungary
  • I. Kovács, University of Debrecen, Debrecen, Hungary
  • É. Lovra, Univesity of Debrecen, Debrecen, Hungary
  • T. Mankovits, University of Debrecen, Debrecen, Hungary
  • I. Medved, Slovak Technical University in Bratislava, Bratislava, Slovakia
  • L. Moga, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • M. Molinari, Royal Institute of Technology, Stockholm, Sweden
  • H. Moravcikova, Slovak Academy of Sciences, Bratislava, Slovakia
  • P. Mukhophadyaya, University of Victoria, Victoria, Canada
  • B. Nagy, Budapest University of Technology and Economics, Budapest, Hungary
  • H. S. Najm, Rutgers University, New Brunswick, United States
  • J. Nyers, Subotica Tech - College of Applied Sciences, Subotica, Serbia
  • B. W. Olesen, Technical University of Denmark, Lyngby, Denmark
  • S. Oniga, North University of Baia Mare, Baia Mare, Romania
  • J. N. Pires, Universidade de Coimbra, Coimbra, Portugal
  • L. Pokorádi, Óbuda University, Budapest, Hungary
  • A. Puhl, University of Debrecen, Debrecen, Hungary
  • R. Rabenseifer, Slovak University of Technology in Bratislava, Bratislava, Slovak Republik
  • M. Salah, Hashemite University, Zarqua, Jordan
  • D. Schmidt, Fraunhofer Institute for Wind Energy and Energy System Technology IWES, Kassel, Germany
  • L. Szabó, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • Cs. Szász, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • J. Száva, Transylvania University of Brasov, Brasov, Romania
  • P. Szemes, University of Debrecen, Debrecen, Hungary
  • E. Szűcs, University of Debrecen, Debrecen, Hungary
  • R. Tarca, University of Oradea, Oradea, Romania
  • Zs. Tiba, University of Debrecen, Debrecen, Hungary
  • L. Tóth, University of Debrecen, Debrecen, Hungary
  • A. Trnik, Constantine the Philosopher University in Nitra, Nitra, Slovakia
  • I. Uzmay, Erciyes University, Kayseri, Turkey
  • T. Vesselényi, University of Oradea, Oradea, Romania
  • N. S. Vyas, Indian Institute of Technology, Kanpur, India
  • D. White, The University of Adelaide, Adelaide, Australia
  • S. Yildirim, Erciyes University, Kayseri, Turkey

International Review of Applied Sciences and Engineering
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International Review of Applied Sciences and Engineering
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