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Comparison of a primal and a dual decomposition for distributed MPC in smart districts

Abstract : This paper deals with energy management in smart districts using distributed model predictive control (DMPC). We investigate two decomposition methods, primal and dual decomposition, for problems where a shared resource has to be distributed optimally amongst sub systems. The objective is to compare these two decomposition methods with a focus on how well they are suited in the context of smart district energy management. In primal decomposition a coordinator layer is directly affecting resource limits to the sub problems whereas in dual decomposition virtual prices are used to stimulate the sub problems to change their resource consumption behavior in a desired way. Both methods are demonstrated to be able to converge to the globally optimal energy distribution in simula- tions, provided that the limit on the shared resource is chosen in a reasonable range. This result is particularly interesting regarding the fact that in the dual decomposition case, the number of degrees of freedom of the coordinator problem is only a fraction of the number of degrees of freedom in primal decomposition
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Contributor : Mazen Alamir Connect in order to contact the contributor
Submitted on : Thursday, July 10, 2014 - 11:59:32 AM
Last modification on : Tuesday, October 19, 2021 - 11:22:23 PM


  • HAL Id : hal-01022355, version 1



Peter Pflaum, Mazen Alamir, Mohamed Yacine Lamoudi. Comparison of a primal and a dual decomposition for distributed MPC in smart districts. SmartGridComm 2014 - 5th IEEE International Conference on Smart Grid Communications, Nov 2014, Venise, Italy. pp.n/c. ⟨hal-01022355⟩



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