Deep Decarbonization of Multi-Energy Systems: A Carbon-Oriented Framework with Cross Disciplinary Technologies

TL;DR

This paper proposes a comprehensive framework for analyzing carbon emissions in rapidly evolving multi-energy systems, integrating cross-disciplinary technologies like game theory, optimization, and machine learning to support decarbonization efforts.

Contribution

It introduces a novel carbon-oriented framework for multi-energy systems and explores how advanced technologies can enhance modeling and analysis of carbon flows.

Findings

Framework effectively models carbon allowances and circulation.

Cross-disciplinary methods improve analysis accuracy.

Supports policy development for decarbonization.

Abstract

The retirement of unabated coal power plants, the plummeting cost of renewable energy technologies, along with more aggressive public policies and regulatory reforms, are occurring at an unprecedented speed to decarbonize the power and energy systems towards the 2030 and 2050 climate goals. This article aims to establish a carbon-oriented framework to examine the role carbon emission is playing within a power grid that is rapidly transitioning to an integrated multi-energy system. We divide the carbon flows in the multi-energy systems into three stages: carbon allowances initialization/allocation, exchanging/pricing, and circulation. Then, we discuss how cross-disciplinary technologies, such as game theory, optimization, and machine learning can facilitate the modeling and analysis of the proposed framework.