A bounding method for solution of economic dispatch problem with uncertain PV power generation

Abstract

In this paper, we propose a parametric quadratic programming method for the day-ahead scheduling of power generation and battery charge cycles, where the prediction uncertainty of power consumption, photovoltaic power generation, and their half-hourly change is modeled as a parameter vector lying in interval boxes. The parametric quadratic programming is formulated as the problem of finding the interval hull of the image of a function of the minimizer. To solve this problem, we apply a monotonicity-based approach and show that the interval hulls can be obtained by mapping extreme points in a set of parameter vectors. Next, we locate the optimal extreme points by moving a parameter vector along the boundary of the set as in simplex method for solving linear programming. The resultant interval hulls represent minimum regulating capacities of fuel generators and inverter of batteries needed for a stable power supply with minimum economic cost.