Chance Constrained Optimal Power Flow Using the Inner-Outer Approximation Approach

Abstract

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. Keywords-Optimal power flow (OPF); chance constrained programming; inner-outer approximation approach; uncertain wind power generation; non-Gaussian distribution. NOMENCLATURE , ijIndices for buses. BSusceptance. () IsPiecewise continuous function.f Objective function.

Archives of Electrical Engineering

“…The idea is to also develop the same for real time applications as demonstrated in [45][46][47][48], in comparison with the real time OPF. The method has to be developed further so that the convergence time is significantly reduced.…”

A Distributed Inter-Phase Coordination Algorithm for Voltage Control With Unbalanced PV Integration in LV Systems

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