Abstract
This paper presents a probabilistic power flow model subject to connection temperature constraints. Renewable
power generation is included and modelled stochastically in order to reflect its intermittent nature. In contrast to conventional
models
that enforce connection current constraints, short-term current overloading is allowed. Temperature constraints are weaker
than current constraints, and hence the proposed model quantifies the overload risk more realistically. Using such a constraint
is justified the more by the intermittent nature of the renewable power source.
Allowing temporary current overloading
necessitates the incorporation of a time domain in our model. This substantially influences the choice of model for the
renewable power source, as we explain. Wind power is modelled by use of an ARMA model, and appropriate accelerations of
the power flow solution technique are chosen. Several IEEE test case examples illustrate the more realistic risk analysis.
An example shows that a current constraint model may overestimate these risks, which may lead to unnecessary over-investments
by grid operators in grid connections.
power generation is included and modelled stochastically in order to reflect its intermittent nature. In contrast to conventional
models
that enforce connection current constraints, short-term current overloading is allowed. Temperature constraints are weaker
than current constraints, and hence the proposed model quantifies the overload risk more realistically. Using such a constraint
is justified the more by the intermittent nature of the renewable power source.
Allowing temporary current overloading
necessitates the incorporation of a time domain in our model. This substantially influences the choice of model for the
renewable power source, as we explain. Wind power is modelled by use of an ARMA model, and appropriate accelerations of
the power flow solution technique are chosen. Several IEEE test case examples illustrate the more realistic risk analysis.
An example shows that a current constraint model may overestimate these risks, which may lead to unnecessary over-investments
by grid operators in grid connections.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of Probabilistic Methods Applied to Power Systems 2012 (PMAPS ) |
| Publisher | IEEE |
| Pages | 494-499 |
| Publication status | Published - 1 May 2012 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Probabilistic power flow
- reliability analysis
- Monte Carlo
- renewable generation
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