TY - GEN

T1 - State Estimation for Unbalanced Three-Phase AC Microgrids Based on Mathematical Programming

AU - Acurio, Byron Alejandro Acuña

AU - Barragán, Diana Estefanía Chérrez

AU - López, Juan Camilo

AU - Grijalva, Felipe

AU - Rodríguez, Juan Carlos

AU - Pereira Da Silva, Luiz Carlos

N1 - Publisher Copyright:
© 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - State estimation (SE) helps to determine the most-likely steady-state operation of microgrids based on field measurements. It is a fundamental data processing tool responsible for supporting and increasing system visibility and filtering errors that may appear in real-time measurements, system topology, and parameters. Hence, it serves as a reliable basis for the energy management system (EMS) infrastructure. Existing SE methods are based on Newton-like algorithms rather than using specific optimization. Nevertheless, SE can always be reduced to a constrained optimization problem, with the objective of minimizing a given criterion, e.g., weighted least squares (WLS) or weighted least absolute value (WLAV). In this context, this paper presents two unbalanced three-phase AC SE methods based on mathematical programming for microgrids. The effectiveness and validity of the proposed state estimation approach are demonstrated on a real microgrid located at the State University of Campinas, in Brazil, and over one widely known IEEE test system. The method can be easily adapted to other microgrids with different configurations, distributed energy resources, and measurements. Results show that the proposed methods report high accuracy, but the state estimator based on WLS is faster than the WLAV.

AB - State estimation (SE) helps to determine the most-likely steady-state operation of microgrids based on field measurements. It is a fundamental data processing tool responsible for supporting and increasing system visibility and filtering errors that may appear in real-time measurements, system topology, and parameters. Hence, it serves as a reliable basis for the energy management system (EMS) infrastructure. Existing SE methods are based on Newton-like algorithms rather than using specific optimization. Nevertheless, SE can always be reduced to a constrained optimization problem, with the objective of minimizing a given criterion, e.g., weighted least squares (WLS) or weighted least absolute value (WLAV). In this context, this paper presents two unbalanced three-phase AC SE methods based on mathematical programming for microgrids. The effectiveness and validity of the proposed state estimation approach are demonstrated on a real microgrid located at the State University of Campinas, in Brazil, and over one widely known IEEE test system. The method can be easily adapted to other microgrids with different configurations, distributed energy resources, and measurements. Results show that the proposed methods report high accuracy, but the state estimator based on WLS is faster than the WLAV.

KW - Microgrids

KW - nonlinear programming problem

KW - state estimation

KW - unbalanced three-phase AC network

UR - http://www.scopus.com/inward/record.url?scp=85151501198&partnerID=8YFLogxK

U2 - 10.1109/ISGT51731.2023.10066353

DO - 10.1109/ISGT51731.2023.10066353

M3 - Contribución a la conferencia

AN - SCOPUS:85151501198

T3 - 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)

BT - 2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2023

Y2 - 16 January 2023 through 19 January 2023

ER -