Conclusion

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This chapter addresses the impact of intermittent wind generation on power system small signal stability. Firstly, the well-known Weibull probability distribution is employed to reveal wind speed uncertainty. According to the Weibull distribution of wind speed, the Monte Carlo simulation technique based probabilistic small signal stability analysis is applied to solve the probability distributions of wind farm power output and the eigenvalues of the state matrix. Finally, the IEEE New England test power system is studies as benchmark to demonstrate the effectiveness and validity of the propose model and method. Based on the numerical simulation results, we can determine the instability probability of the power system with the uncertainty and randomness of wind power consideration. And from viewpoint of small signal stability, the most suitable integration position for wind farm can be determined as well.

EM mode

Frequency

Damping ratio

EM relevant ratio

Most relevant generator

Stability

Mean

Std

Mean

Std

Mean

Std

1

1.5021

0.0000

0.0506

0.0002

22.9116

0.1119

G8

100%

2

1.4816

0.0003

0.0613

0.0002

36.1465

3.9023

G7

100%

3

1.4569

0.0006

0.0642

0.0010

10.2773

0.3156

G4

100%

4

1.2794

0.0001

0.0363

0.0005

29.5096

0.2265

G8

100%

5

1.2642

0.0013

0.0133

0.0026

91.3249

25.3277

G2

100%

6

1.1370

0.0024

0.0375

0.0001

32.0537

0.0459

G6

100%

7

1.0394

0.0040

0.0084

0.0027

35.6480

1.9408

G9

100%

8

0.9817

0.0012

0.0066

0.0019

48.0187

8.0547

G6

100%

9

0.6554

0.0020

0.0030

0.0033

52.8691

4.1706

G10

60.9%

Table 3. Properties of EM oscillation modes with wind farm integration into bus20

Table 3. Properties of EM oscillation modes with wind farm integration into bus20

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Renewable Energy Eco Friendly

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable.

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