Abstract | ||
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This paper deals with hierarchical model predictive control (MPC) of distributed systems. A three-level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or consuming units can be exploited in a smart-grid solution. The objective is to accommodate load variations on the grid, arising from varying consumption and natural variations in power production, e.g. from wind turbines. The approach presented is based on quadratic optimisation and has low algorithmic complexity as well as good scalability. In particular, the proposed design methodology facilitates plug-and-play addition of subsystems without controller redesign. The method is verified by simulating a three-level smart-grid power control system for a small isolated power grid. |
Year | DOI | Venue |
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2010 | 10.1109/CDC.2010.5717038 | Decision and Control |
Keywords | Field | DocType |
control system synthesis,predictive control,quadratic programming,smart power grids,wind turbines,aggregators,autonomous units,consumption systems,distributed systems,hierarchical model predictive control,high level MPC controller,load variations,low algorithmic complexity,online MPC-like algorithm,quadratic optimisation,resource distribution,small isolated power grid,smart-grid electric power production,three-level smart-grid power control system,wind turbines | Electric power,Control theory,Smart grid,Computer science,Control theory,Model predictive control,Control engineering,Hierarchical database model,Grid,Wind power,Scalability | Conference |
ISSN | ISBN | Citations |
0743-1546 | 978-1-4244-7745-6 | 7 |
PageRank | References | Authors |
1.05 | 4 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jan Dimon Bendtsen | 1 | 46 | 22.56 |
Klaus Trangbaek | 2 | 15 | 4.03 |
Jakob Stoustrup | 3 | 274 | 52.57 |