Keynote Lectures

Abstract
This presentation focusses on how societies can design and achieve resilient and fully decarbonization energy systems based on renewable energy. The presentation addresses a set of methods and criteria to design Smart Energy Systems, while considering the context of 100% renewable energy on a national level. Countries should handle locally what concerns local demands, and at the same time acknowledge the international context when discussing resources and industrial and transport demands. Following such approach will also lead to a resilient energy solution. To illustrate the method, it is applied to the cases of Denmark and European within the context of a global fully decarbonized energy system.

The goals of the Danish Government supported by the Danish Parliament is to reduce Greenhouse gas emissions by 70% in 2030 and to achieve a net zero emission society by 2050. Moreover, due to the war in Ukraine, there is also a strong wish for a resilient energy supply. This presentation includes a list of theoretical and methodological considerations as well as a concrete proposal on how such targets can be implemented. It is highlighted that already now one must think beyond 2030 to prepare for the next step to achieve a full decarbonization by 2040 or 2050. It is also highlighted that a country such as Denmark must consider how to include its share of international shipping and aviation as well as how to design a solution with Denmark’s share of sustainable biomass resources. 

Moreover, the presentation includes the results of detailed hourly modelling of the EU “A Clean Planet” scenarios for a fully decarbonized Europe in 2050 and compare it to a “smart energy systems” alternative. The case illustrates how the focus on a fully sector-coupling as expressed in a smart energy systems approach will lead to higher energy efficiency and the identification of a more affordable green transition in Europe.

Abstract
Smart world is receiving a great attention from academia, industry and government thanks to the flourish and the advance of Internet of Things (IoT) and Information and Communication Technologies (ICTs). In this context, smart cities are envisioned to be an elementary unit of a smart and sustainable world, where all aspects related to cyber, physical and social world will be interconnected in an intelligent and eco-friendly fashion. Bringing together the physical realm with the cyber one consisting of a wide umbrella of novel computing technologies, the vision of a smart city as a Cyber-Physical System in a networked perspective is enabled, where the communication infrastructure is the core for a smart connectivity among all the involved “things”. By virtue of the above, smart cities can monitor the real world in real time and are able to provide smart services and solutions to local residents and travelers in terms of services. Therefore, the objective of the talk is to deliver the essence of smart cities by focusing  on some of their main constitutive pillars, i.e., i) smart transportation, ii) smart energy, iii) smart community. The combination of these elements will allow an enhancement of operations performance efficiency compared with the ones achievable in a regular city, as well as of the provided quality of services, thus promoting the transition towards a sustainable and eco-friendly smart world. Moreover, the need of moving from IoT to Green-IoT will be pointed out, which is crucial to reduce the harmful effects of IoT in terms of toxic pollution, consumed energy and generation of e-waste. Latest developments in the technical literature on this field will be discussed in order to provide future research insights for researchers and practitioners. Furthermore, open challenges and barriers to the next green world transition will be summarized.

Abstract
Offering predictable journey times is important to the uptake of sustainable road transportation including future public, shared, and on-demand mobility services and to on-time delivery of goods [1]. The emergence of connected and automated vehicles, the deployment of Internet-of-Things technologies, and the availability of machine-learning based optimization techniques will enable both monitoring of and exercising fine-grained control over individual vehicles either directly or indirectly. This in turn offers the possibility of deploying fundamentally different approaches to traffic management offering high quality of service and, especially, increased end-to-end travel-time reliability [1].

This talk will consider how connected and automated vehicles can enable the use of traffic shaping mechanisms, in particular, our proposed slot-based driving model, to provide predictability in travel times. We will consider how multi-agent deep reinforcement learning can be harnessed to deliver appropriate optimization strategies while taking account of the scale, complexity, and inherent non-stationarity of traffic systems and adapting to the many transient perturbations that effect traffic flow. 

[1] Vinny Cahill and Ivana Dusparic, ClearWay: Advancing Deep Reinforcement Learning and Swarm Intelligence to Optimize Travel-Time Reliability in Mixed Traffic, SFI Frontiers for the Future Programme award number 21/FFP-A/8957 Research Plan, 2022.

Abstract
The autonomous car has been proposed as a huge breakthrough in modern transport for many years. However, this breakthrough has not yet arrived, and the industry seems to have wasted years and money on providing a solution that is still a long way off. However, sometimes the wood cannot be seen for the trees, and we forget how the autonomous vehicle is already today solving important mobility problems of the 21st century, a century where mobility advances are moving in precisely the opposite direction to that of the vehicle, whether private or public.