Robust distributed MPC for load frequency control of uncertain power systems
Reliable Load frequency control (LFC) is crucial to the operation and design of modern electric power systems. However, the power systems are always subject to uncertainties and external disturbances. Considering the LFC problem of a multi-area interconnected power system, this paper presents a robu...
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| Published in | Control engineering practice Vol. 56; pp. 136 - 147 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.11.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0967-0661 1873-6939 |
| DOI | 10.1016/j.conengprac.2016.08.007 |
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| Summary: | Reliable Load frequency control (LFC) is crucial to the operation and design of modern electric power systems. However, the power systems are always subject to uncertainties and external disturbances. Considering the LFC problem of a multi-area interconnected power system, this paper presents a robust distributed model predictive control (RDMPC) based on linear matrix inequalities. The proposed algorithm solves a series of local convex optimization problems to minimize an attractive range for a robust performance objective by using a time-varying state-feedback controller for each control area. The scheme incorporates the two critical nonlinear constraints, e.g., the generation rate constraint (GRC) and the valve limit, into convex optimization problems. Furthermore, the algorithm explores the use of an expanded group of adjustable parameters in LMI to transform an upper bound into an attractive range for reducing conservativeness. Good performance and robustness are obtained in the presence of power system dynamic uncertainties.
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•A robust DMPC algorithm for interconnected power system is proposed.•The mathematic model for load frequency control of power system is established.•The robustness is studied based on parameter and structure uncertainties.•Performance of the algorithm is verified under the load change and uncertainties. |
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| ISSN: | 0967-0661 1873-6939 |
| DOI: | 10.1016/j.conengprac.2016.08.007 |