Risk assessment in power system using multi-criteria decision making (MCDM) methods
In recent years, immense power system outage events have happened across the world. This is not exceptional to the Malaysia power system whereby on 27 Jun 2013 the system blackout occurred in the state of Sarawak, due to sudden dropping of frequency. Hence, power system risk assessment has become an...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2013
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| Online Access: | http://eprints.uthm.edu.my/6840/1/24p%20CAROLINE%20DAME%20SIAGIAN.pdf http://eprints.uthm.edu.my/6840/2/CAROLINE%20DAME%20SIAGIAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6840/3/CAROLINE%20DAME%20SIAGIAN%20WATERMARK.pdf |
| Summary: | In recent years, immense power system outage events have happened across the world. This is not exceptional to the Malaysia power system whereby on 27 Jun 2013 the system blackout occurred in the state of Sarawak, due to sudden dropping of frequency. Hence, power system risk assessment has become an important and mandatory task in planning, operation, maintenance and asset management of utilities. There have been efforts devoted in searching for new methods and procedures that effectively evaluate the risk of a power system. The objective of this study is to rank and determine the most common cause of power loss outages in the grid. This study implements multi criteria decision-making methods such as Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). For data collection, it employed interviews of key participants, review of documents including unpublished official reports and annual reports. From the data collected there are four criteria identified, namely Duration Time (min), Estimated Maximum Loss of load (MW), Estimated Energy No Supplied (MW-min) and System Minutes. On the other hand, seven causes of power loss outages are identified, they are Treat To System Security, Equipment Failure, Fire or Explosion, Switching Risk, Tower Collapse, Accelerated Ageing of Equipment and Supervisory Control System Failure. Results of data analysis show that both methods have identified that Equipment Failure is the major cause, followed by Supervisory Control System Failure. |
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