The Near-Optimal Feasible Space of a Renewable Power System Model

TL;DR

This paper explores the near-optimal solutions of a renewable European electricity system model, revealing diverse investment options and key infrastructure requirements for cost-effective, sustainable power system planning.

Contribution

It applies the MGA methodology to systematically analyze the near-optimal feasible space of a complex renewable power system model, highlighting persistent features and diversity of solutions.

Findings

Many near-optimal solutions exist with similar costs.

Offshore or onshore wind, hydrogen storage, and transmission are essential.

A 0.5% cost deviation allows for diverse investments.

Abstract

Models for long-term investment planning of the power system typically return a single optimal solution per set of cost assumptions. However, typically there are many near-optimal alternatives that stand out due to other attractive properties like social acceptance. Understanding features that persist across many cost-efficient alternatives enhances policy advice and acknowledges structural model uncertainties. We apply the modeling-to-generate-alternatives (MGA) methodology to systematically explore the near-optimal feasible space of a completely renewable European electricity system model. While accounting for complex spatio-temporal patterns, we allow simultaneous capacity expansion of generation, storage and transmission infrastructure subject to linearized multi-period optimal power flow. Many similarly costly, but technologically diverse solutions exist. Already a cost deviation of 0.5% offers a large range of possible investments. However, either offshore or onshore wind energy along with some hydrogen storage and transmission network reinforcement are essential to keep costs within 10% of the optimum.