Under the umbrella of the PAC project, a range of publications have been produced by various constellations of consortium partners. Find an overview of these below, with relevant download links and a brief summary.
In February 2022 RGI and Hitachi Energy co-organised an online Modellers’ Exchange Workshop ‘‘Accelerating full decarbonisation: Resource optimisation in energy infrastructure planning’’ that brought together more than thirty participants from across Europe and beyond. This report summarises the outcome of this workshop. It introduces the optimal capacity expansion planning model developed by Hitachi Energy, presents the main initial findings and gives an overview of the discussions held with the invited guests.
Among the proposed policies under the “Fit for 55” package, the revision of the Renewable Energy Directive (RED III) is one of the most relevant policy initiatives to secure the transition to a 100% renewables-based energy system. This policy brief relies on the results of the Paris Agreement Compatible (PAC) scenario to benchmark the provisions of the proposed revised RED III against the 1.5°C objective of the Paris Agreement.
The establishment of an open source culture offers an effective way of ensuring transparency and coordinating research, thereby reducing delays in system transformation and accelerating the decarbonisation effort. This document makes the case for open data within energy system modelling, describing the current state of affairs, providing an introduction into fundamental facts and detailing the many advantages of an open source culture.
how civil society can involve more on grid planning processes for renewables, drawing examples from Europe, Australia, Chile, Japan and Vietnam.
This policy brief by the Renewables Grid Initiative synthesises key takeaways from discussions that took place on November 18, 2020 as part of ‘100% RES in all sectors by 2040? – Exchange of European NGOs and TSO’s about the PAC scenario’. The event was held to understand how the PAC scenario is useful for the TSO community, to learn which assumptions are perceived as most challenging, and to discuss opportunities on how to move forward.
A central objective of the PAC Project was to learn how working on scenarios can become a more collaborative process. This Report introduces and evaluates the different elements of collaboration which were at the heart of the project.
CAN Europe and the European Environmental Bureau (EEB) have extracted key recommendations for lawmakers from the PAC scenario. These are meant to serve as guideposts in the ongoing negotiations relating to the European Green Deal and the Recovery Fund.
The PAC Scenario - as a first comprehensive climate and energy roadmap for Europe, drafted by a broad range of civil society organisations - remains a living document. As such, there are questions which still need to be answered through the PAC Scenario modelling. This outlook document includes some open questions which we hope to address in the near future through ongoing dialogue between civil society, energy industry, academia and politics as we jointly search for answers in order to develop a broad-based, climate-neutral energy system.
The PAC scenario was developed by CAN Europe and the EEB under the banner of the PAC project. At its core, the Scenario is an attempt to construct a European-wide energy scenario which is aligned with the Paris Agreement’s objective to limit global warming to 1.5°C and which embodies the policy demands of civil society. In doing this, it suggests a trajectory with:
The PAC Scenario can be downloaded in full by clicking here.
Click here to see an overview of highlights from the PAC scenario.
Click here to download datasets.
As the only pan-European assessments of energy infrastructure projects, the TYNDPs - Ten Year Network Development Plans - produced by ENTSO-E and ENTSOG, have a strong guiding function in decisions about future investements in energy infrastructure. A central part of the PAC project was concerned with reviewing the TYNDP scenarios and their assumptions.