Abstract
Component condition and substation (S/S) reliability have a material impact on the cost of customer interruptions in electricity distribution systems (DSs). However, these factors are not usually considered within distribution system reconfiguration (DSR) problem formulations, because of the lack of a readily available methodology. This paper presents such a method, making use of component condition scores which are now mandatory for distribution system operators (DSOs) in the UK. Based on these condition scores, condition-based failure rate can be calculated for each component. S/S reliability is a function of component condition, S/S configuration and the network upstream of the S/Ss. The reliability of the S/S then has an impact on the reliability indices of each load point (LP) it supplies. These factors are combined to deliver a better informed algorithm for DSR, which is verified through its application on two DSs. The annual savings, compared to the formulation that neglects component condition and S/S reliability, can be in the order of tens of thousands of U.S. dollars for a single DS.
Highlights
Customer interruptions in power systems commonly occur within Distribution Systems (DSs) [1,2]
A minimal cut set is a set of components which, when all of them are out of service, an outage is caused to a specific load point (LP)
This paper proposes a new, better informed, methodology for DS reconfiguration (DSR), which minimizes the total cost of active power losses and expected customer interruption cost (ECOST) by making use of component condition data and considering S/S reliability
Summary
Customer interruptions in power systems commonly occur within Distribution Systems (DSs) [1,2]. The second option (integer encoding) considers that the network consists of a number of loops and each decision variable represents the integer index of the branch that breaks each loop; in this case, the length of the state vector is defined by the number of loops These two options are compared in [20], and it is shown that the second alternative outperforms the first one in optimization time and number of objective function evaluations. In the case of a planned maintenance of an S/S transformer or if new condition data become available to the DSO, the methodology presented in this paper can be implemented in order to find a better informed optimal network configuration for the given time interval.
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