Abstract
The dynamic tariff (DT) method is designed for the
distribution system operator (DSO) to alleviate congestions that
might occur in a distribution network with high penetration of
distributed energy resources (DERs). Uncertainty management is
required for the decentralized DT method because the DT is de-
termined based on optimal day-ahead energy planning with
forecasted parameters such as day-ahead energy prices and en-
ergy needs which might be different from the parameters used by
aggregators. The uncertainty management is to quantify and
mitigate the risk of the congestion when employing the DT
method, which is achieved by firs
tly formulating the problem as a
chance constrained two-level optimization and then solving the
problem through an iterative procedure. Two case studies were
conducted to demonstrate the efficacy of the uncertainty man-
agement of DT method.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Power Systems |
| Volume | 31 |
| Issue number | 6 |
| Pages (from-to) | 4340-4347 |
| ISSN | 0885-8950 |
| DOIs | |
| Publication status | Published - 2016 |
Bibliographical note
Copyright 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Keywords
- Chance constrained program
- Congestion man- agement
- Distribution system opera tor (DSO)
- Distributed energy resources (DERs)
- Uncertainty management
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