in case of wind power velocity and locations and in Solar power irradiation and temperature depends upon location and time. these are stochastic variables
1.Uncertainty Modeling for the Management of Distributed Generation Units using PSO
Pappala V.S., Elrich I.
This paper addresses a multistage stochastic model for the operation of distributed generation (DG) units under stochastic load demands. The stochastic load demands have a significant effect on the economic model of the DG units. The uncertainties are modeled as scenario trees. But as the number of decision making stages increase, the scenario tree becomes extremely large, which leads to complex computation. Therefore a novel approach to generate a scenario tree using classical particle swarm optimization (PSO) approach is presented. The resulting multistage nonlinear stochastic model is solved using adaptive PSO.
in case of wind power velocity and locations and in Solar power irradiation and temperature depends upon location and time. these are stochastic variables
As far as I know, in online studies, Point estimate methods have more advantages than Monte Carlo simulation methods for solving the stochastic power flow problem cause of much lower scenarios needed to be considered . However, when it comes to offline studies such as optimal reactive power dispatch in distribution systems, is this proportion comprehensible yet?
What kinds of point estimate schemes would lead to better results? how & where can I find complete information about these specific schemes?