Details
| Original language | English |
|---|---|
| Pages | 6340-6345 |
| Number of pages | 6 |
| Publication status | Published - 28 Jun 2017 |
| Externally published | Yes |
| Event | 2017 IEEE 56th Annual Conference on Decision and Control (CDC) - Melbourne, Australia Duration: 12 Dec 2017 → 15 Dec 2017 |
Conference
| Conference | 2017 IEEE 56th Annual Conference on Decision and Control (CDC) |
|---|---|
| Period | 12 Dec 2017 → 15 Dec 2017 |
Abstract
Fast power fluctuations pose increasing challenges on the existing control structure for power networks. One challenge is how to incorporate economic performance and constraint satisfaction in the operation. Current state of the art controllers are based on online steady-state optimization algorithms, which guarantee optimal steady-state performance. A natural extension of this trend is to consider economic model predictive control (EMPC), a dynamic optimization method, which can give guarantees on transient economic performance and constraint satisfaction. We show that the real time economic dispatch problem can be posed as an EMPC problem and provide corresponding transient guarantees for feasibility, stability and economic performance. Next, we show how the corresponding optimization problem can be solved online with dual distributed optimization and study stopping conditions due to real time requirements. This leads to an inexact solution of the optimization problem and we provide guarantees for this inexact distributed EMPC. Finally, we present simulation results showing constraint satisfaction and superior economic performance of the EMPC approach compared to state of the art solutions.
ASJC Scopus subject areas
- Decision Sciences(all)
- Decision Sciences (miscellaneous)
- Mathematics(all)
- Control and Optimization
- Engineering(all)
- Industrial and Manufacturing Engineering
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2017. 6340-6345 Paper presented at 2017 IEEE 56th Annual Conference on Decision and Control (CDC).
Research output: Contribution to conference › Paper › Research
}
TY - CONF
T1 - Real time economic dispatch for power networks
T2 - 2017 IEEE 56th Annual Conference on Decision and Control (CDC)
AU - Köhler, Johannes
AU - Müller, Matthias A.
AU - Allgöwer, Frank
AU - Li, Na
N1 - Funding information: The authors would like to thank the German Research Foundation (DFG) for support of this work within grant AL 316/11 ? 1, the Cluster of Excellence in Simulation Technology (EXC 310/1), NSF ECCS 1608509, NSF CAREER 1553407, and APAR-E NODES program.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - Fast power fluctuations pose increasing challenges on the existing control structure for power networks. One challenge is how to incorporate economic performance and constraint satisfaction in the operation. Current state of the art controllers are based on online steady-state optimization algorithms, which guarantee optimal steady-state performance. A natural extension of this trend is to consider economic model predictive control (EMPC), a dynamic optimization method, which can give guarantees on transient economic performance and constraint satisfaction. We show that the real time economic dispatch problem can be posed as an EMPC problem and provide corresponding transient guarantees for feasibility, stability and economic performance. Next, we show how the corresponding optimization problem can be solved online with dual distributed optimization and study stopping conditions due to real time requirements. This leads to an inexact solution of the optimization problem and we provide guarantees for this inexact distributed EMPC. Finally, we present simulation results showing constraint satisfaction and superior economic performance of the EMPC approach compared to state of the art solutions.
AB - Fast power fluctuations pose increasing challenges on the existing control structure for power networks. One challenge is how to incorporate economic performance and constraint satisfaction in the operation. Current state of the art controllers are based on online steady-state optimization algorithms, which guarantee optimal steady-state performance. A natural extension of this trend is to consider economic model predictive control (EMPC), a dynamic optimization method, which can give guarantees on transient economic performance and constraint satisfaction. We show that the real time economic dispatch problem can be posed as an EMPC problem and provide corresponding transient guarantees for feasibility, stability and economic performance. Next, we show how the corresponding optimization problem can be solved online with dual distributed optimization and study stopping conditions due to real time requirements. This leads to an inexact solution of the optimization problem and we provide guarantees for this inexact distributed EMPC. Finally, we present simulation results showing constraint satisfaction and superior economic performance of the EMPC approach compared to state of the art solutions.
UR - http://www.scopus.com/inward/record.url?scp=85046151572&partnerID=8YFLogxK
U2 - 10.1109/CDC.2017.8264615
DO - 10.1109/CDC.2017.8264615
M3 - Paper
SP - 6340
EP - 6345
Y2 - 12 December 2017 through 15 December 2017
ER -