Code for the paper "Distributed photovoltaics provides key benefits for a highly renewable European energy system"
This repository contains the notebooks to reproduce figures in the main text and supplementary.
In this paper, we aim to redefine the role of distributed solar photovoltaic systems in facilitating the green transition. Rooftop PV is projected to be a key contributor to future energy landscape, but is often poorly represented in energy models due to its distributed nature. It has higher costs compared to utility PV, but offers additional advantages, e.g. in terms of social acceptance. We model the European power network with a high spatial resolution of 181 nodes and a 2-hourly temporal resolution. The modeling of distribution and transmission network allows the representation of power distribution losses and differentiates between utility and distributed generation and storage. Three scenarios, including a sector-coupled scenario with heating, transport, and industry are investigated. The results show that incorporating distributed solar PV leads to total system cost reduction in all scenarios. Also, underestimating the expenses and losses incurred by the distribution grid seriously undermines the profitability of distributed solar PV. The achieved cost reductions (1.4% for the power sector and 1.9-3.7% for the sector-coupled scenario) primarily stem from demand peak reduction because of self-consumption from distributed solar. This reduces the required distribution grid capacity and enhances self-sufficiency for countries. The role of distributed PV is noteworthy in the sector-coupled scenario and is helped by other distributed technologies including heat pumps and electric vehicle batteries.
notebookscontains the Jupyter notebooks used for the evaluation of results. Attention: The code is customised for networks of this study, so care should be taken when using it to produce similiar figures for PyPSA network files.
The notebooks use pre-solved networks (main scenario files avialble at zenodo:https://zenodo.org/records/11277299) to produce the figures from the paper. PyPSA-Eur-Sec v0.6.0 is used to produce the networks.