Zhao Liu
ABSTRACT
In the operation of a medium-voltage distribution system, any weakness in the system topology, facility reliability, technology application and interruption management can set a limit to the reliability indices. As the planning scheme of the distribution system is mostly formulated based on standards or guides, the influence of technology and interruption management on reliability is rarely considered at the planning stage. This can cause excessive investment to system construction and facility upgrades for meeting a reliability target.
This paper introduces a practical approach for undertaking reliability-based planning for medium-voltage distribution systems, which is supplementary to the standard-based planning. The proposed approach enables optimisation strategies that cover system topology, facility, technology and interruption management to be formulated as part of the planning scheme. One of the key tasks in the reliability-based planning is to perform sensitivity study, which provides quantitative support to the formulation of optimisation strategies.
This research focuses on five parameters, including the number of interconnected feeders, failure outage rate, number of feeders equipped with distributed automation, live-line working rate and scheduled outage rate. A sensitivity study of the system average interruption duration index (SAIDI) to these parameters is performed in order to assess the effectiveness of the corresponding improving measures. Results show that both strengthening the management of scheduled interruptions and enhancing the application of live-line working can be more effective than reinforcing the system topology when SAIDI is larger than 12 hours/customer. These two measures become less effective as SAIDI decreases. In contrast, reinforcing the system topology, increasing facility reliability and applying distribution automation techniques become increasingly effective as SAIDI decreases. When SAIDI is below 3 hours/customer, reinforcing the system topology becomes the most effective improving measure.
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