42,228 research outputs found
Chance Constrained Optimal Power Flow Using the Inner-Outer Approximation Approach
In recent years, there has been a huge trend to penetrate renewable energy
sources into energy networks. However, these sources introduce uncertain power
generation depending on environmental conditions. Therefore, finding 'optimal'
and 'feasible' operation strategies is still a big challenge for network
operators and thus, an appropriate optimization approach is of utmost
importance. In this paper, we formulate the optimal power flow (OPF) with
uncertainties as a chance constrained optimization problem. Since uncertainties
in the network are usually 'non-Gaussian' distributed random variables, the
chance constraints cannot be directly converted to deterministic constraints.
Therefore, in this paper we use the recently-developed approach of inner-outer
approximation to approximately solve the chance constrained OPF. The
effectiveness of the approach is shown using DC OPF incorporating uncertain
non-Gaussian distributed wind power
Strong Stationarity Conditions for Optimal Control of Hybrid Systems
We present necessary and sufficient optimality conditions for finite time
optimal control problems for a class of hybrid systems described by linear
complementarity models. Although these optimal control problems are difficult
in general due to the presence of complementarity constraints, we provide a set
of structural assumptions ensuring that the tangent cone of the constraints
possesses geometric regularity properties. These imply that the classical
Karush-Kuhn-Tucker conditions of nonlinear programming theory are both
necessary and sufficient for local optimality, which is not the case for
general mathematical programs with complementarity constraints. We also present
sufficient conditions for global optimality.
We proceed to show that the dynamics of every continuous piecewise affine
system can be written as the optimizer of a mathematical program which results
in a linear complementarity model satisfying our structural assumptions. Hence,
our stationarity results apply to a large class of hybrid systems with
piecewise affine dynamics. We present simulation results showing the
substantial benefits possible from using a nonlinear programming approach to
the optimal control problem with complementarity constraints instead of a more
traditional mixed-integer formulation.Comment: 30 pages, 4 figure
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