Probabilistic load flow using Monte Carlo techniques for distribution
networks with photovoltaic generators
Solar Energy, (2007)Abstract
Connections of distributed generation (DG) systems to distribution
networks are increasing in number, though they may often be associated
with the need of costly grid reinforcements or new control issues
to maintain optimal operation. Appropriate analysis tools are required
to check distribution networks operating conditions in the evolving
scenario. Load flow (LF) calculations are typically needed to assess
the allowed DG penetration level for a given network in order to
ensure, for example, that voltage and current limits are not exceeded.
The present paper deals with the solution of the LF problem in distribution
networks with photovoltaic (PV) DG. Suitable models for prediction
of the active power produced by PV DG units and the power absorbed
by the loads are to be used to represent the uncertainty of solar
energy availability and loads variation. The proposed models have
been incorporated in a radial distribution probabilistic load flow
(PLF) program that has been developed by using Monte Carlo techniques.
The developed program allows probabilistic predictions of power flows
at the various sections of distribution feeders and voltage profiles
at all nodes of a network. After presenting theoretical concepts
and software implementation, a practical case is also discussed to
show the application of the study in order to assess the maximum
PV peak power that can be installed into a distribution network without
violating voltage and current constraints. A comparison between Deterministic
Load Flow (DLF) and PLF analyses is also performed.