Cooperative Model Predictive Control Scheme for Dispersed Smart Inverters at the Grid Edge

Fard, Amin Y.; Shadmand, Mohammad B.

doi:10.1109/tpec48276.2020.9042565

Cooperative Model Predictive Control Scheme for Dispersed Smart Inverters at the Grid Edge

Conference · Sat Feb 01 04:00:00 EST 2020 · 2020 IEEE Texas Power and Energy Conference (TPEC)

DOI:https://doi.org/10.1109/tpec48276.2020.9042565· OSTI ID:1908556

Fard, Amin Y. ^[1]; Shadmand, Mohammad B.

University of Illinois Chicago

Growing number of distributed energy resources (DERs) requires cutting-edge control schemes to ensure uniform but not identical involvement of DERs to address rapid fluctuations on voltage of the grid clusters. Designing such control schemes for a grid with high penetration of DERs connected various clusters is complex and depends on physical configuration of the clusters themselves. This paper proposes a two-layered cooperative model predictive control scheme for fleet of dispersed smart inverters connected to a three-phase grid cluster located at the edge of a grid cluster. The upper layer of the controller ensures cooperative operation of fleet of smart inverters to perform voltage regulation and address voltage fluctuations in the grid cluster; while the lower level controller guarantees each individual inverter obeys the dictated references for active/reactive powers by the upper layer controller. In addition, the proposed twolayered controller has low voltage ride through (LVRT) capability to support the grid clusters during voltage sags. By employing the proposed control approach, the smart inverters will inject desired active/reactive powers based on circumstance of the entire cluster while guaranteeing proper power curtailment among the generation units. The control scheme is verified by simulation.

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Research Organization:: Kansas State University

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

DOE Contract Number:: EE0008767

OSTI ID:: 1908556

Report Number(s):: DOE-KSU-8767

Conference Information:: Journal Name: 2020 IEEE Texas Power and Energy Conference (TPEC)

Country of Publication:: United States

Language:: English

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