Abstract

This paper presents an energy management system for smart microgrids (MGs) based on hierarchical model predictive control (HiMPC). The HiMPC comprises two levels. On the lower level load-frequency control is realized on a short time scale while on the upper level economic dispatch and unit commitment are implemented on a long time scale. HiMPC allows integrating these functionalities over different time scales while regarding constraints (e.g. power ratings) and predictions (e.g. on renewable generation and load) as well as rejecting disturbances (e.g. due to volatile renewable generation) based on a systematic model- and optimization-based design. The HiMPC problem is formulated as a mixed-integer linear program which can be solved efficiently using standard solvers. The energy management system is evaluated for a smart MG of a company with a focus on grid integration of electric vehicles.

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