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ASSESSING AND IMPROVING RECOMMENDATIONS FOR LOCAL POWER QUALITY EFFICIENCY FOR INDUSTRIAL PLANTS WITH THE HELP OF REAL DATA
- Source :
- Volume: 4, Issue: 1 12-20, International Journal of Energy and Smart Grid
- Publication Year :
- 2020
- Publisher :
- Zülküf GÜLSÜN, 2020.
-
Abstract
- The Turkish grid system is under big dynamic changes. Renewables are continuously increasing, distribution privatization was completed. There are many participants of electricity system of Turkey. To synchronise all these needs scientific rules and regulations to be obeyed. On the other hand, although many rules, there is no any statistical data about how system operates effectively. What are the industrial plants faced with? Industrial plants connected to the national distribution or transmission grid at medium voltage level are really exposed to various grid events that affect firstly production efficiency, equipment, system failure and unexpected malfunctioning. Without data, there is no way to analysis and make clear definition of grid events. Recorded data for a long time in the point of common coupling will be used to evaluate existing status and to estimate next ones. In this paper, comparative power quality comparison will be analysed for 12 industrial plants distributed localized at five different industrial grid points. It is aimed to the seven different regions of our country compared to the facilities connected to the national system and compare them with a point from abroad. With this study, Turkish power quality intensity is realized by site data for next care of private sectors, private electric companies and industrial plants, and to give numerical data to literature.
- Subjects :
- Engineering, Electrical and Electronic
business.industry
Computer science
Turkish
media_common.quotation_subject
Distribution (economics)
Mühendislik, Elektrik ve Elektronik
Environmental economics
Private sector
Discount points
Grid
language.human_language
power,quality,grid,events,statistic,sag
Renewable energy
language
Quality (business)
business
Statistic
media_common
Subjects
Details
- Language :
- English
- ISSN :
- 25480332 and 26367904
- Database :
- OpenAIRE
- Journal :
- Volume: 4, Issue: 1 12-20, International Journal of Energy and Smart Grid
- Accession number :
- edsair.doi.dedup.....02f0c238271491129c8d8dfdd5e7e7ee