Work

Managing Risk using Rolling Forecasts in Energy-Limited and Stochastic Energy Systems

Year: 2024

Type: conference-paper

Abstract: We study risk-aware linear policy approx-imations for the optimal operation of an energy system with stochastic wind power, storage, and limited fuel. The resulting problem is a sequential decision-making problem with rolling forecasts. In addition to a risk-neutral objective, this paper formulates two risk-aware objectives that control the conditional value-at-risk of system cost and the buffered probability of exceeding a predefined threshold of unserved load. The resulting policy uses a parameter-modified cost function approximation that reduces the computational load compared to the direct inclusion of those risk measures in the problem objective. We demonstrate our method on a numerical case study.

Source: North American Power Symposium (NAPS)

DOI: 10.1109/naps61145.2024.10741683

Authors: Thomas Mortimer, Robert Mieth

Institution: Rutgers, The State University of New Jersey

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: green

Funder: Danmarks Tekniske Universitet