TY - CONF

T1 - Exact Power Constraints in Smart Grid Control

A1 - Trangbæk,K

A1 - Petersen,Mette Højgaard

A1 - Bendtsen,Jan Dimon

A1 - Stoustrup,Jakob

AU - Trangbæk,K

AU - Petersen,Mette Højgaard

AU - Bendtsen,Jan Dimon

AU - Stoustrup,Jakob

PB - I E E E I E E E Control Systems Society

PY - 2011

Y1 - 2011

N2 - This paper deals with hierarchical model<br/>predictive control (MPC) of smart grid systems. The<br/>objective is to accommodate load variations on the grid,<br/>arising from varying consumption and natural variations<br/>in the power production e.g. from wind turbines. This<br/>balancing between supply and demand is performed by<br/>distributing power to consumers in an optimal manner,<br/>subject to the requirement that each consumer receives<br/>the specific amount of energy the consumer is entitled<br/>to within a specific time horizon. However, in order to<br/>do so, the high-level controller requires knowledge of<br/>how much energy the consumers can receive within a<br/>given time horizon. In this paper, we present a method<br/>for computing these bounds as convex constraints that<br/>can be used directly in the optimisation. The method is<br/>illustrated on a simulation example that uses measured<br/>wind data as load variation, and fairly realistic consumer<br/>models. The example illustrates that the exact bounds<br/>computed by the proposed method leads to a better power<br/>distribution than a conventional, conservative approach<br/>in case of fast changes in the load.

AB - This paper deals with hierarchical model<br/>predictive control (MPC) of smart grid systems. The<br/>objective is to accommodate load variations on the grid,<br/>arising from varying consumption and natural variations<br/>in the power production e.g. from wind turbines. This<br/>balancing between supply and demand is performed by<br/>distributing power to consumers in an optimal manner,<br/>subject to the requirement that each consumer receives<br/>the specific amount of energy the consumer is entitled<br/>to within a specific time horizon. However, in order to<br/>do so, the high-level controller requires knowledge of<br/>how much energy the consumers can receive within a<br/>given time horizon. In this paper, we present a method<br/>for computing these bounds as convex constraints that<br/>can be used directly in the optimisation. The method is<br/>illustrated on a simulation example that uses measured<br/>wind data as load variation, and fairly realistic consumer<br/>models. The example illustrates that the exact bounds<br/>computed by the proposed method leads to a better power<br/>distribution than a conventional, conservative approach<br/>in case of fast changes in the load.

UR - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6160539

U2 - 10.1109/CDC.2011.6160539

DO - 10.1109/CDC.2011.6160539

JO - I E E E Conference on Decision and Control. Proceedings

JF - I E E E Conference on Decision and Control. Proceedings

SN - 0743-1546

ER -