01588nas a2200181 4500008004100000245012600041210006900167520094300236653002401179653002301203653001501226653002901241100001901270700001801289700001901307700001901326856006101345 2020 eng d00aDistributed model predictive control for energy management in a network of microgrids using the dual decomposition method0 aDistributed model predictive control for energy management in a 3 a
Summary This paper deals with the application of model predictive control (MPC) to optimize power flows in a network of interconnected microgrids (MGs). More specifically, a distributed MPC (DMPC) approach is used to compute for each MG how much active power should be exchanged with other MGs and with the outer power grid. Due to the presence of coupled variables, the DMPC approach must be used in a suitable way to guarantee the feasibility of the consensus procedure among the MGs. For this purpose, we adopt a tailored dual decomposition method that allows us to reach a feasible solution while guaranteeing the privacy of single MGs (ie, without having to share private information like the amount of generated energy or locally consumed energy). Simulation results demonstrate the features of the proposed cooperative control strategy and the obtained benefits with respect to other classical centralized control methods.
10adistributed systems10adual decomposition10amicrogrids10amodel predictive control1 aRazzanelli, M.1 aCrisostomi, E1 aPallottino, L.1 aPannocchia, G. uhttps://onlinelibrary.wiley.com/doi/abs/10.1002/oca.2504