Title: Chance-Constrained AC Optimal Power Flow Integrating HVDC Lines and Controllability,
Abstract: The integration of large-scale renewable generation has major implications on
the operation of power systems, two of which we address in this paper. First,
system operators have to deal with higher degrees of uncertainty. Second, with
abundant potential of renewable generation in remote locations, they need to
incorporate the operation of High Voltage Direct Current lines (HVDC). This
paper introduces an optimization tool that addresses both challenges by
incorporating; the full AC power flow equations and chance constraints to
address the uncertainty of renewable infeed, HVDC modeling for point-to-point
lines, and optimizing generator and HVDC corrective control policies in
reaction to uncertainty. The main contributions are twofold. First, we
introduce a HVDC line model and the corresponding HVDC participation factors in
a chance-constrained AC-OPF framework. Second, we modify an existing algorithm
for solving the chance-constrained AC optimal power flow to allow for
optimization of the generation and HVDC participation factors. Using realistic
wind forecast data, and a 10 bus system with one HVDC line and two wind farms,
we demonstrate the performance of our algorithm and show the benefit of
controllability.