Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

Yi Zong; Daniel Kullmann; Anders Thavlov; Oliver Gehrke; Henrik W. Bindner

doi:10.1109/TSG.2011.2177282

Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

Yi Zong, Daniel Kullmann, Anders Thavlov, Oliver Gehrke, Henrik W. Bindner

Department of Electrical Engineering

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

This paper introduces an experimental platform (SYSLAB) for the research on advanced control and power system communication in distributed power systems and one of its components-an intelligent office building (PowerFlexHouse), which is used to investigate the technical potential for active load management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching of demand and supply can be achieved. With this demand side control study, it is expected that MPC strategy for active load management can dramatically raise energy efficiency and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

Original language	English
Journal	I E E E Transactions on Smart Grid
Volume	3
Issue number	2
Pages (from-to)	1055-1062
ISSN	1949-3053
DOIs	https://doi.org/10.1109/TSG.2011.2177282
Publication status	Published - 2012

Keywords

Active load management
Distributed power system
Flexible consumption
Model predictive control
Wind power penetration

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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title = "Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration",

abstract = "This paper introduces an experimental platform (SYSLAB) for the research on advanced control and power system communication in distributed power systems and one of its components-an intelligent office building (PowerFlexHouse), which is used to investigate the technical potential for active load management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching of demand and supply can be achieved. With this demand side control study, it is expected that MPC strategy for active load management can dramatically raise energy efficiency and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.",

keywords = "Active load management, Distributed power system, Flexible consumption, Model predictive control, Wind power penetration, Intelligente energisystemer",

author = "Yi Zong and Daniel Kullmann and Anders Thavlov and Oliver Gehrke and Bindner, {Henrik W.}",

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Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration. / Zong, Yi; Kullmann, Daniel; Thavlov, Anders; Gehrke, Oliver ; Bindner, Henrik W.

In: I E E E Transactions on Smart Grid, Vol. 3, No. 2, 2012, p. 1055-1062.

Research output: Contribution to journal › Journal article › Research › peer-review

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AU - Bindner, Henrik W.

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AB - This paper introduces an experimental platform (SYSLAB) for the research on advanced control and power system communication in distributed power systems and one of its components-an intelligent office building (PowerFlexHouse), which is used to investigate the technical potential for active load management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching of demand and supply can be achieved. With this demand side control study, it is expected that MPC strategy for active load management can dramatically raise energy efficiency and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

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