Broad ranges of investment configurations for renewable power systems, robust to cost uncertainty and near-optimality

Fabian Neumann; Tom Brown

doi:10.1016/j.isci.2023.106702

Broad ranges of investment configurations for renewable power systems, robust to cost uncertainty and near-optimality

iScience. 2023 Apr 21;26(5):106702. doi: 10.1016/j.isci.2023.106702. eCollection 2023 May 19.

Authors

Fabian Neumann^{1

2}, Tom Brown^{1

2}

Affiliations

¹ Department of Digital Transformation in Energy Systems, Institute of Energy Technology, Technische Universität Berlin (TUB), Einsteinufer 25 (TA 8), 10587 Berlin, Germany.
² Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.

Abstract

Achieving ambitious ${C O}_{2}$ emission reduction targets requires energy system planning to accommodate societal preferences, such as transmission reinforcements or onshore wind parks, and acknowledge uncertainties in technology cost projections among many other uncertainties. Current models often solely minimize costs using a single set of cost projections. Here, we apply multi-objective optimization techniques in a fully renewable European electricity system to explore trade-offs between system costs and technology deployment for electricity generation, storage, and transport. We identify ranges of cost-efficient capacity expansion plans incorporating future technology cost uncertainties. For example, we find that some grid reinforcement, long-term storage, and large wind capacities are important to keep costs within 8% of least-cost solutions. Near the cost optimum a technologically diverse spectrum of options exist, allowing policymakers to make trade-offs regarding unpopular infrastructure. Our analysis comprises 50,000+ optimization runs, managed efficiently through multi-fidelity surrogate modeling techniques using sparse polynomial chaos expansions and low-discrepancy sampling.

Keywords: Energy Modelling; Energy Systems; Energy management; Energy policy; Energy resources.