IMPROVING POWER SYSTEM STABILITY AFTER CONTINGENCY OCCURRENCE ON THE BASIS OF DISTRIBUTED ARTIFICIAL INTELLIGENCE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

KHANZADEH M.H.; NABATIRAD M.R.; ASHRAFI A.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Advanced Defense Science and Technology Year:2016 | Volume:6 | Issue:4 Page(s): 245-253

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

2,335

Download:

Cites:

Information Journal Paper

Title

IMPROVING POWER SYSTEM STABILITY AFTER CONTINGENCY OCCURRENCE ON THE BASIS OF DISTRIBUTED ARTIFICIAL INTELLIGENCE

Author(s)

KHANZADEH M.H. | NABATIRAD M.R. | ASHRAFI A. | Issue Writer Certificate

Keywords

POWER SYSTEM SECURITYQ2

MULTI AGENT SYSTEMQ2

DISTRIBUTED ARTIFICIAL INTELLIGENCEQ2

WIDE AREA CONTROLQ2

Abstract

Considering the importance of power networks in national security, power system stability under critical conditions such as occurrence of contingencies is the most important concern of power system engineers and government. In this area, employing DISTRIBUTED ARTIFICIAL INTELLIGENCE (DAI) theory and also Wide Area Monitoring, Protection And Control (WAMPAC) infrastructures may help to create a flexible organization where provides a robust system against contingency occurrence. This study proposes an adaptive structure on the basis of MULTI AGENT SYSTEM (MAS). In this context, an algorithm has been proposed which helps the control system to save power system from collapse after detection of wide area voltage violation. Also, in order to verify the proposed algorithm, Dig SILENT software has been employed to simulate and the results are compared with conventional structures such as central control system and also unsupervised control structure.

Cites

No record.

References

No record.

Cite

APA: Copy

KHANZADEH, M.H., NABATIRAD, M.R., & ASHRAFI, A.. (2016). IMPROVING POWER SYSTEM STABILITY AFTER CONTINGENCY OCCURRENCE ON THE BASIS OF DISTRIBUTED ARTIFICIAL INTELLIGENCE. (JOURNAL OF ADVANCED DEFENCE SCIENCE AND TECHNOLOGY) JOURNAL OF PASSIVE DEFENCE SCIENCE AND TECHNOLOGY, 6(4), 245-253. SID. https://sid.ir/paper/167377/en

Vancouver: Copy

KHANZADEH M.H., NABATIRAD M.R., ASHRAFI A.. IMPROVING POWER SYSTEM STABILITY AFTER CONTINGENCY OCCURRENCE ON THE BASIS OF DISTRIBUTED ARTIFICIAL INTELLIGENCE. (JOURNAL OF ADVANCED DEFENCE SCIENCE AND TECHNOLOGY) JOURNAL OF PASSIVE DEFENCE SCIENCE AND TECHNOLOGY[Internet]. 2016;6(4):245-253. Available from: https://sid.ir/paper/167377/en

IEEE: Copy

M.H. KHANZADEH, M.R. NABATIRAD, and A. ASHRAFI, “IMPROVING POWER SYSTEM STABILITY AFTER CONTINGENCY OCCURRENCE ON THE BASIS OF DISTRIBUTED ARTIFICIAL INTELLIGENCE,” (JOURNAL OF ADVANCED DEFENCE SCIENCE AND TECHNOLOGY) JOURNAL OF PASSIVE DEFENCE SCIENCE AND TECHNOLOGY, vol. 6, no. 4, pp. 245–253, 2016, [Online]. Available: https://sid.ir/paper/167377/en

Related Journal Papers