Open AccessInvestigation of Power Networks and their Patterns by Mathematical methods in order to Voltage Stability Enhancement
Author(s) -
Seyed Morteza Moghimi,
Ali Bostani,
Abolfazl Elahimanesh
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1391/1/012159
Subject(s) - limit (mathematics) , voltage , electric power system , stability (learning theory) , distributed generation , power (physics) , computer science , control theory (sociology) , voltage regulation , engineering , electrical engineering , mathematics , renewable energy , physics , machine learning , mathematical analysis , control (management) , quantum mechanics , artificial intelligence
Authors in the research paper has considered IEEE 14-bus and 34-bus test network for creation generation and load patterns. This paper aims at analysing the potential impacts that distributed generation (DG) might have on voltage stability of electrical power networks. It is expected that increasing amounts of new generation technologies will be connected to electrical power systems in the near future. Most of these technologies are considerably smaller scale than conventional synchronous generators. In this paper, the impact of DG pattern (size and location of DG) on the voltage stability of two test system is investigated. The simulation methodology is discussed as well. It is found that the effects of DG the voltage stability of a power system strongly depend on the size and location of the distributed generators. The results show that install of DG on the weak bus, improve loadability limit and voltage stability and decrease loss of system. By investigating and reviewing the results of similar patterns in these two systems, the different generation and load patterns impact mechanism of DG units over the behaviour of the systems in terms loadability limit and voltage stability is achieved.