Location

Hilton Hawaiian Village, Honolulu, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

3-1-2024 12:00 AM

End Date

6-1-2024 12:00 AM

Description

Modern active distribution systems are experiencing wide operating conditions due to distributed energy resources and prosumers with variable patterns. Faults can create loss of substantial parts of feeders. In both cases, optimizing the configuration of the distribution system can result in great savings. We define two problems: (a) optimal feeder reconfiguration to optimize operations under normal conditions, and (b) optimal feeder reconfiguration to maximize service following the occurrence of a fault. In this paper, we formulate both problem as an optimization problem of the dynamic programming variety. In the first problem, the objective is to minimize losses or minimize operational cost, while the objective of the second problem is to minimize the number of interrupted customers or minimize the total power not served. The solution for both problems is expressed in terms of an optimal sequence of switch control operations, subject to the operational constraints of the switches. The dynamic programming approach is very flexible and can integrate all pertinent operational constraints. However, it suffers from the Curse of Dimensionality. To mitigate the issue, state reduction technique is adopted in a successive dynamic programming algorithm to limit the dimensionality of the problem. The proposed algorithm has been tested on distribution systems to demonstrate

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Jan 3rd, 12:00 AM Jan 6th, 12:00 AM

Optimal Reconfiguration of Distribution Networks via Dynamic Programming

Hilton Hawaiian Village, Honolulu, Hawaii

Modern active distribution systems are experiencing wide operating conditions due to distributed energy resources and prosumers with variable patterns. Faults can create loss of substantial parts of feeders. In both cases, optimizing the configuration of the distribution system can result in great savings. We define two problems: (a) optimal feeder reconfiguration to optimize operations under normal conditions, and (b) optimal feeder reconfiguration to maximize service following the occurrence of a fault. In this paper, we formulate both problem as an optimization problem of the dynamic programming variety. In the first problem, the objective is to minimize losses or minimize operational cost, while the objective of the second problem is to minimize the number of interrupted customers or minimize the total power not served. The solution for both problems is expressed in terms of an optimal sequence of switch control operations, subject to the operational constraints of the switches. The dynamic programming approach is very flexible and can integrate all pertinent operational constraints. However, it suffers from the Curse of Dimensionality. To mitigate the issue, state reduction technique is adopted in a successive dynamic programming algorithm to limit the dimensionality of the problem. The proposed algorithm has been tested on distribution systems to demonstrate

https://aisel.aisnet.org/hicss-57/es/resilient_networks/6