This invention discloses a reactive
power optimization method for
distribution networks based on probabilistic
power flow sensitivity analytical transformation, belonging to the field of power
system optimization and dispatching technology. The method includes: considering the
impact of source-load power uncertainty on distribution network dispatching, constructing a reactive
power optimization model based on chance constraints, and using probabilistic
power flow sensitivity to characterize the probability distributions of
voltage and
branch power random variables respectively; linearizing the quadratic nonlinear
branch security constraints using a regular polygon approximation method to decouple the optimization variables from the random variables; establishing
analytical expressions for
voltage and
branch security chance constraints through affine transformation of probabilistic
power flow sensitivity; and analytically transforming the nonlinear chance constraints into deterministic constraints based on probability transformation theory, transforming the original problem into a mixed-integer second-order
cone programming model for solution. This invention can fully tap the potential of photovoltaic reactive
power regulation, significantly improve
voltage stability and reduce network losses, while also having a computational efficiency
advantage over the traditional sample mean method.