Name
Abstract | ||
|---|---|---|
This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of noncontrollable resources. Optimality and convergence of the proposed algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem. |
Year | Venue | Field |
|---|---|---|
2017 | IEEE Global Conference on Signal and Information Processing | Convergence (routing),Mathematical optimization,Computer science,Flow (psychology),Regular polygon,AC power,Distributed generation,Dynamic problem,Metering mode,Linearization |
DocType | ISSN | Citations |
Conference | 2376-4066 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yijian Zhang | 1 | 1 | 1.02 |
| Emiliano Dall'Anese | 2 | 360 | 38.11 |
| Mingyi Hong | 3 | 1533 | 91.29 |