# Risk Neutral Reformulation Approach to Risk Averse Stochastic Programming

## TL;DR

This paper presents a method to reformulate risk-averse multistage stochastic programming problems into risk-neutral ones by changing the probability measure, demonstrated through an application to power system operation planning.

## Contribution

It introduces a novel change-of-measure approach that simplifies risk-averse problems into risk-neutral forms, facilitating easier analysis and solution.

## Key findings

- The change-of-measure approach effectively emphasizes extreme scenarios.
- Application to power system planning shows improved problem handling.
- Reformulation benefits include computational advantages and better scenario representation.

## Abstract

The aim of this paper is to show that in some cases risk averse multistage stochastic programming problems can be reformulated in a form of risk neutral setting. This is achieved by a change of the reference probability measure making ``bad" (extreme) scenarios more frequent. As a numerical example we demonstrate advantages of such change-of-measure approach applied to the Brazilian Interconnected Power System operation planning problem.