Small-signal stability analysis of DFIG based wind power system using teaching learning based optimization

Chatterjee, Shamik; Naithani, Abishek; Mukherjee, V.

doi:10.1016/j.ijepes.2015.11.113

Cited by 29 publications

(14 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The output power of variable speed WTs is about 2% to 6% more than the output power of constant speed WTs. 13 Thus, various studies have been conducted on this type of generators. [14][15][16] The behavior of WTs to disturbances is regarded as one of the major issues and should be studied, especially when the power of the WT increased.…”

Section: Literature Reviewmentioning

confidence: 99%

“…We can represent (13) as ΔV c = k(m 0 ΔV dc +V dc0 Δm). Linearization of (38) and (39) results in the following equations.…”

Section: System Linearizationmentioning

confidence: 99%

“…Emami et al introduced an algorithm to solve this problem with estimation techniques. The output power of variable speed WTs is about 2% to 6% more than the output power of constant speed WTs . Thus, various studies have been conducted on this type of generators .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling of integrated power system with wind turbine based on a doubly fed induction generator and solid oxide fuel cell for small‐signal stability analysis

Safari

Badr

Farrokhifar

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary This paper aims to propose the small‐signal model of a wind turbine (WT) based on a doubly fed induction generator (DFIG) and a solid oxide fuel cell (SOFC) into the transmission network for dynamic stability analysis of the integrated system. The principal goal is to introduce the novel small‐signal model of the hybrid power system in the presence of the WT and SOFC power plants for analyzing of electromechanical oscillations. Therefore, the modeling of each generation unit of the integrated system in the same framework is illustrated. Besides, a comprehensive mathematical model is demonstrated from WT and SOFC units integrated with a synchronous generator (SG) and the infinite bus system. Based on the proposed model, the linear analysis is illustrated under different conditions for stability studies. Moreover, this study presents the influence of different portions of WT and SOFC units on the small‐signal stability. The simulation results represent the performance of the suggested model.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…We can represent (13) as ΔV c = k(m 0 ΔV dc +V dc0 Δm). Linearization of (38) and (39) results in the following equations.…”

Section: System Linearizationmentioning

confidence: 99%

See 1 more Smart Citation

Modeling of integrated power system with wind turbine based on a doubly fed induction generator and solid oxide fuel cell for small‐signal stability analysis

Safari

Badr

Farrokhifar

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…Also, the bus used for connecting the wind farm index was identified by calculating the placement index. Chatterjee et al (2016) designed a teaching learning-based optimization (TLBO) technique for analyzing the signal stability of DFIG wind power system. Here, the dynamic performance of the DFIG system was controlled by the use of proportional-integral (PI) controllers.…”

Section: Related Workmentioning

confidence: 99%

An enhanced particle swarm optimization algorithm for improving the renewable energy penetration and small signal stability in power system

Renuka¹,

Reji²,

Sreedharan³

2018

Renewables

View full text Add to dashboard Cite

In power systems, increasing the renewable energy penetration with small signal stability is one of the demanding and critical tasks in recent days. This research work aims to develop a multistage optimization technique, namely particle swarm optimization (PSO), for improving both the energy penetration and small signal stability. Here, the wind and solar power sources are considered, and its penetration is maximized by satisfying the grid requirements such as the bus voltage, line flows, and real and reactive power generation within the limit. This work includes two stages: in the first stage, PSO algorithm is implemented for maximizing the renewable energy penetration to the test systems. Then, in the second stage, the small signal stability of the systems is improved with maximum renewable energy penetration in which the best locations for connecting the wind farm are identified by using the calculation of wind farm placement index and solar generation is fixed by considering voltage and bus load absorption capability. During simulation, the proposed method is tested and validated by using IEEE 14-bus standard system, and the 220 kV Kerala (India) grid practical system with the solar and wind power. Moreover, various measures such as power generation, load and bus voltage are evaluated for two different case studies. In this evaluation, it is proved that the renewable energy sources are safely integrated with the power system with increased energy penetration and improved small signal stability. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

show abstract

“…Mehta et al (2015) found that the optimization of controller parameters of a DFIG-based wind generation system employing particle swarm optimization technique minimized the oscillations in rotor currents and electromagnetic torque. Chatterjee et al (2016) in their work used teaching learning based optimization (TLBO) algorithm to optimize the gains of PI controllers associated with DFIG and showed that the TLBO provides superior end results than PSO. Most of the works described above deals with the small signal stability enhancement of wind integrated system; however no such work points to an optimized artificial intelligence based system with least computational cost.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of small signal stability of a DFIG-based wind power system using fuzzy logic control

Renuka¹,

Reji²,

Sreedharan³

2016

Int. J. Eng. Sci. Tech

View full text Add to dashboard Cite

This paper proposes fuzzy logic controllers for enhancing the small signal stability of DFIG-based wind integrated power system. The test system used is single machine infinite bus system integrated with conventional proportional-integral controllers. The fuzzy logic controllers provide optimum proportional and integral gains under various operating conditions namely wind speed and grid strength. The effects of strong and weak grid strengths have been taken into account with short circuit level of 40 MVA and 16 MVA, respectively. The obtained result justifies that the damping ratio and there by the small signal stability of such a system have been enhanced considerably by the action of fuzzy logic controllers. The generalization can be enlarged to multi-machine systems in various dynamic conditions.

show abstract

Small-signal stability analysis of DFIG based wind power system using teaching learning based optimization

Cited by 29 publications

References 21 publications

Modeling of integrated power system with wind turbine based on a doubly fed induction generator and solid oxide fuel cell for small‐signal stability analysis

Modeling of integrated power system with wind turbine based on a doubly fed induction generator and solid oxide fuel cell for small‐signal stability analysis

An enhanced particle swarm optimization algorithm for improving the renewable energy penetration and small signal stability in power system

Enhancement of small signal stability of a DFIG-based wind power system using fuzzy logic control

Contact Info

Product

Resources

About