Interval Load Flow for Uncertainty Consideration in Power Systems Analysis

Wallisson C. Nogueira, Lina Paola Garcés Negrete and Jesús M. López-Lezama
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Wallisson C. Nogueira: Electrical, Mechanical and Computer Engineering School, Federal University of Goiás, Av. Universitária No. 1488, Goiânia 74605-010, Brazil
Lina Paola Garcés Negrete: Electrical, Mechanical and Computer Engineering School, Federal University of Goiás, Av. Universitária No. 1488, Goiânia 74605-010, Brazil
Jesús M. López-Lezama: Grupo en Manejo Eficiente de la Energía (GIMEL), Departamento de Ingeniería Eléctrica, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín 050010, Colombia

Energies, 2021, vol. 14, issue 3, 1-14

Abstract: Modern power systems must deal with a greater degree of uncertainty in power flow calculation due to variations in load and generation introduced by new technologies. This scenario poses new challenges to power system operators which require new tools for an accurate assessment of the system state. This paper presents an interval load flow (ILF) approach for dealing with uncertainty in power system analysis. A probabilistic load flow (PLF), based on Monte Carlo Simulation (MCS), was also implemented for comparative purposes. The ILF and PLF are used to estimate the network states. Both methods were implemented in Python ® using the IEEE 34-bus, IEEE 69-bus and 192-bus Brazilian distribution system. The results with the proposed ILF on the aforementioned benchmark test systems proved to be compatible with that of the MCS, evidencing the robustness and applicability of the proposed approach.

Keywords: uncertainty; probabilistic load flow; interval load flow; Monte Carlo Simulation (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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