How can climate policy lead to behavioural change? ChangeAble develops new knowledge aimed at accelerating behavioural change, provides insight into which individual, social and contextual factors stimulate sustainable behaviour, and how and when policy can effectively leverage them. ChangeAble also provides insight into how tipping points can be reached by improved policy timing for more widespread and faster sustainable behavioural change. ChangeAble identifies, develops and tests interventions to promote changes in social conventions in five policy areas. In this way, ChangeAble contributes to more effective, efficient, acceptable and just climate policy by making better use of behavioural knowledge in policy.

The ENBARK+ proposal develops a combination of zonal and nodal pricing methods combined with energy- and power-based modeling techniques for metropolitan distribution systems that have to handle an increasing amount of renewables and the embedding of electrical vehicles. A particular focus will be given to the characteristics of the Amsterdam area with many different potential pricing zones. The area includes Schiphol airport, office buildings areas, residential areas (new and old), and so on, whereas there is also a new network of charging stations for electric vehicles. The infrastructure is relatively old, and embedding of new elements such as charging stations and solar panels will put pressure on the grid. Thus, it is necessary to coordinate the charging and possibly the storage of surplus of electricity in e.g. batteries of the electric vehicles. The ENBARK+ proposal aims to use and develop physical modeling methods building further on the developments of the ENBARK project, but now specifically for an Amsterdam like distribution system. In addition, a combination of nodal and zonal pricing will be added to those models. In part B we propose to integrate our findings with the SMARTEST project, in order to include social relevance in our developments.

High-precision manufacturing pushes the limits of what is possible with conventional manufacturing systems. The development of the new generation of high-precision manufacturing systems relies on detailed understanding of the process disturbances which cause variation in the end-product. This project aims at developing models for control of manufacturing processes which can be used for interpreting small variations in the process due to product-to-product disturbances. Such accurate and mature models can only be developed through integration of knowledge from high-fidelity physics-based models with knowledge obtained from large streams of sensor data. Integration of models and sensor data is key for the development of novel data analytic tools providing crucial causal information to the product-to-product variations which can subsequently be used by our novel data-driven control systems to pre-empt and to remove such variations in real-time.

Modern power systems, driven by renewable energy, exhibit complex, emergent phenomena that existing scientific methods cannot address. This proposal aims to create the largest academic, real-time electromagnetic transient (EMT) simulator to provide a virtual power system for experiments. The research focuses on developing new analytical frameworks, investigating complex dynamics and control, and exploring decentralised markets, and adaptive regulatory frameworks. The infrastructure, accessible to consortium partners and international researchers, supports detailed modelling, system dynamics understanding, and designing essential tools and processes for future power systems. This multidisciplinary approach promises scientific breakthroughs to generate new theories for future power systems.