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Title: Probabilistic reliability assessment of transmission systems
Author: Alali, Dawood
ISNI:       0000 0004 5919 8314
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2015
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Power system reliability is defined as the ability of a power system to perform its function of maintaining supply without allowing network variables (e.g. voltage, component loading and frequency) to stray too far from the standard ranges. Traditionally over many decades, reliability has been assessed using deterministic criteria, e.g., ‘N-1’ or ‘N-2’ standards under prescribed severe system demand levels. However, using the so-called worst-case deterministic approach does not provide explicitly an assessment of the probability of failure of the component or system, and the likelihood of the outages is treated equally. On the other hand, a probabilistic security assessment may offer advantages by considering (i) a statistical description of the performance of the system together with (ii) the application of historical fault statistics that provide a measure of the probability of faults leading to component or system outages. The electrical transmission system, like other systems, is concerned with reducing different risks and costs to within acceptable limits. Therefore, a more precise algorithm of a probabilistic reliability assessment of electrical transmission systems offers an opportunity to achieve such efficiency. This research work introduces the concept of applying the Line Overloading Risk Index (LORI) to assess one of the risks to transmission systems, namely, line overloading. Line failure or outage due to line overloading is catastrophic; they may lead to either load interruptions or system blackout. Some recent studies have focused on the assessment of the LORI; however, such research has been restricted to the analysis of system with very few intermediate demand levels and an assumed constant line thermal rating. This research work aims to extend the evaluation of the LORI through a comprehensive evaluation of transmission system performance under hour-by-hour system demand levels over a oneyear period, for intact systems, as well as ‘N-1’, ‘N-2’. In addition, probable hourly line thermal ratings have also been evaluated and considered over an annual cycle based on detailed meteorological data. In order to accomplish a detailed analysis of the system reliability, engineering data and historical line fault and maintenance data in real transmission systems were employed. The proposed improved probabilistic reliability assessment method was evaluated using a software package, namely, NEPLAN, thus making it possible to simulate different probable load flow cases instead of assuming a single ‘worst case scenario’. An automated process function in NEPLAN was developed using an extensive programming code in order to expedite the load flow modelling, simulation and result reporting. The successful use of the automation process to create multiple models and apply different contingencies, has made possible this probabilistic study which would not have been possible using a ‘manual’ simulation process. When calculating the LORI, the development of a Probabilistic Distribution Function (PDF) for line loading, line thermal rating and system demand was essential and useful. The developed algorithm takes into consideration the likelihood of events occurring in addition to severity, which offers opportunity for more efficient planning and operation of transmission systems. Study cases performed on real electric transmission systems in Dubai and the GB have demonstrated that the developed algorithm has potential as a useful tool in system planning and operation. The research presented in this thesis offers an improved algorithm of probabilistic reliability assessment for transmission systems. The selected index, along with the developed algorithm, can be used to rank the transmission lines based on the probabilistic line overloading risk. It provides valuable information on the degree of line overloading vulnerability for different uncertainties.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TK Electrical engineering. Electronics Nuclear engineering