Remote Renewable Hubs For Carbon-Neutral Synthetic Fuel Production

TL;DR

This paper introduces a graph-based optimization framework to analyze the economics of remote renewable energy supply chains for carbon-neutral synthetic fuel production, focusing on North Africa to Europe methane delivery.

Contribution

It presents a novel hypergraph abstraction for strategic planning of remote renewable energy supply chains, enabling integrated modeling of complex interactions on an hourly basis.

Findings

Synthetic methane cost under 150 EUR/MWh by 2030 for 10 TWh annual supply.

The integrated model captures technology interactions and supply chain dynamics.

Sensitivity analysis highlights key economic parameters affecting costs.

Abstract

This paper studies the economics of carbon-neutral synthetic fuel production from renewable electricity in remote areas where high-quality renewable resources are abundant. To this end, a graph-based optimisation modelling framework directly applicable to the strategic planning of remote renewable energy supply chains is proposed. More precisely, a hypergraph abstraction of planning problems is introduced, wherein nodes can be viewed as optimisation subproblems with their own parameters, variables, constraints and local objective. Nodes typically represent a subsystem such as a technology, a plant or a process. Hyperedges, on the other hand, express the connectivity between subsystems. The framework is leveraged to study the economics of carbon-neutral synthetic methane production from solar and wind energy in North Africa and its delivery to Northwestern European markets. The full supply chain is modelled in an integrated fashion, which makes it possible to accurately capture the interaction between various technologies on an hourly time scale. Results suggest that the cost of synthetic methane production and delivery would be slightly under 150 EUR/MWh (higher heating value) by 2030 for a system supplying 10 TWh annually and relying on a combination of solar photovoltaic and wind power plants, assuming a uniform weighted average cost of capital of 7%. A comprehensive sensitivity analysis is also carried out in order to assess the impact of various techno-economic parameters and assumptions on synthetic methane cost, including the availability of wind power plants, the investment costs of electrolysis, methanation and direct air capture plants, their operational flexibility, the energy consumption of direct air capture plants, and financing costs.