Load flow computations for (integrated) Transmission and Distribution systems

A literature review

Report (2020)
Author(s)

M.E. Kootte (TU Delft - Numerical Analysis)

J.E. Romate (TU Delft - Numerical Analysis)

C. Vuik (TU Delft - Numerical Analysis)

Research Group
Numerical Analysis
Copyright
© 2020 M.E. Kootte, J.E. Romate, Cornelis Vuik
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Publication Year
2020
Language
English
Copyright
© 2020 M.E. Kootte, J.E. Romate, Cornelis Vuik
Research Group
Numerical Analysis
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Abstract

Electrical
power systems are complex systems and traditionally modeled in two separate
systems. Power is generated at the transmission system and at several
substations converted to the distribution systems. The increasing amount of
generation produced at distribution level can eventually effect the
transmission network. An integrated model of both systems can help studying
these effects and prevent harmful events on the power system. Transmission and
Distribution systems differ significantly from each other. Where transmission systems
are assumed to be balanced and therefore modeled as a single-phase system, the distribution
systems are in general unbalanced and should be modeled in three-phase. Furthermore,
high R/X ratios of distribution lines, the lower voltage level, the radial
structure and the presence of unbalanced loading lead to different solution
techniques. Connecting these two systems pose complications for both the
solution method and the connection method. In this report, we present several
methods to solve the integrated Transmission-Distribution system. One of them
is to omit the simplifications we can make in a transmission system and solve
both systems as a three-phase system. Another method is to use a master-slave
splitting approach and solve both systems iteratively, using a boundary state.
A last method is building an interconnected network which solves the system at
once, respecting both the transmission and distribution conditions. Some
artificial currents and voltages have to be injected on the boundary. We
compare the different methods on CPU-time, convergence, accuracy and complexity
and present the preferable method for the specific network criteria.

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