Toward a flexible scenario generation tool for stochastic renewable energy analysis

Abstract

A renewable scenario generation tool is proposed for supporting multiple scenario generation methods. This tool can model a variety of dependence structures, allowing users more flexibility to meet the needs of accurately modeling the uncertainty in renewable energy. The proposed tool describes uncertainty in measurements obtained from different renewable sources located in different sites using marginal distributions in histograms. To capture dependence in modeling and sampling, the proposed tool is thus composed of two key components: (i) distribution and dependence modeled by proper copula; (ii) dependent scenario generation by the Latin hypercube sampling method. The scenarios produced rely on dependence modeling as well as the sampling technique used to capture dependence. The proposed scenario generation tool is numerically tested with actual wind power output measurements and forecasted power outputs.