Fast Calculation Method of Probabilistic Optimal Power Flow for Renewable Dominated Power Grid Based on Improved Convex Relaxation

The existing probabilistic optimal power flow (POPF) studies mainly focus on the design and improvement on probabilistic calculation methods, which may be difficult to improve the computational efficiency of POPF as POPF is a nonconvex and nonlinear programming problem under uncertainty. Therefore, this paper centers on renewable-dominated AC-DC power grid and proposes a POPF model considering uncertainties associated with wind and solar power. To efficiently solve the POPF model, an improved convex relaxation is proposed to address the nonconvex and nonlinear power flow equations and reformulate the nonlinear POPF model as convex one. Furthermore, the Nataf transformation is adopted to address the correlations of non-normal distribution and then a Monte Carlo Simulation based Latin Hypercube sampling technique is developed to solve the convex POPF model. Finally, the effectiveness of the proposed improved convex relaxation based POPF method is demonstrated by a set of case results tested on the modified IEEE 39-bus, 118-bus, and 500-bus systems.