Consensus-Based Model Predictive Control for Active Power and Voltage Regulation in Active Distribution Networks

Gianluca Antonelli, Giuseppe Fusco and Mario Russo ()
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Gianluca Antonelli: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43, 03043 Cassino, Italy
Giuseppe Fusco: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43, 03043 Cassino, Italy
Mario Russo: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio 43, 03043 Cassino, Italy

Energies, 2024, vol. 17, issue 17, 1-19

Abstract: In this paper, a consensus-based model predictive control (Cb-MPC) scheme is proposed to control the active power and voltage at all nodes in grid-connected active distribution networks (ADNs) with multiple distributed energy resources (DERs). The proposed design methodology is based on a multiple-input multiple-output (MIMO) model of an ADN which accounts for both the internal and external interactions among the control loops of the DERs. To achieve the control objective, each DER unit is equipped with a controller–observer system. In particular, the observer implements the consensus algorithm to estimate the collective system state by exchanging data only with its neighbors. The scope of the controller is to solve the MPC optimal problem based on its collective state estimate, and, due to the presence of an integral term in the control action, it is robust against any unknown scenarios of the ADN, which are represented by uncertainty in the model parameters. The results of numerical simulations validate the effectiveness of the proposed method in the presence of unknown changes in the operating conditions of the ADN and of communication using a sample and hold function.

Keywords: active distribution networks; distributed energy resources; MIMO models; distributed model predictive control; parameter uncertainty; simulations (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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