related metrics presents an opportunity to trigger policy learning, action, and cooperation to bring cities closer to sustainable development.
Sustainable development in smart cites and smart islands for faster energy transition and democratization of public utilities
Moderator: Prof. Goran Krajačić
Smart islands and smart cites are becoming places with advanced technological solutions and complex integration of energy, water and environmental systems. Widespread use of the best available ICT solutions provides many opportunities to collect, analyse in interpret large amounts of data which further opens up space for use of many tools based on AI and machine learning. On the one hand the tools are used for forecasting and planning of systems development, their operation and maintenance while on the other they are supporting development of future markets, new services and most important the tools could speed up energy transition and democratization of production, distribution and storage systems for the many of public utilities. The panel will discuss current projects, applied solutions as well as future developments and barriers in application of sustainable solutions in smart cites and smart islands.
Generating electricity using offshore renewable energies and its connection to the grid and local storage is one of the main challenges to speed up the energy transition in the next years. Furthermore, digitalization strategies and technologies are one of the main pillars of the Next Generation EU fund to support member states impacted by the Covid-19 pandemic. The integration of these two topics is essential to optimize the energy flexibility of islands, where onshore renewable energy sources are often only partially accessible due to natural and landscaping constraints, and, on the other hand, energy consumptions are generally characterized by a high seasonality. In this context, my speech will briefly introduce models, best practices and solutions currently investigated in some EU funded research projects, including machine learning and neural networks models to assess and forecast marine renewables potentialities, as well as virtual power systems and digital twin models to match renewable generation and energy needs, trying to trigger a discussion on how to facilitate the energy transition of islands using marine renewables and digitalization strategies and technologies.
ICT solutions supported by AI and machine learning provide opportunities to collect, analyse, and improve system development planning. It plays a role in speed up energy transition and facilitates future development and improved efficiency.
The advantages of “smart” are generally known; however, the benefits are not absolute in all cases. Several challenges associated with Smart Cities and Smart Island have to be considered in tackling the potential cons.
These include (i) waste generation and (ii) the rebound effect of the rapid development, as well as the security issues. The short introduction intended to highlight the challenges of Smart Cities and Island from these three aspects, with examples given. It leads to the discussion of
(a) Is smart technology sustainable – enhancing recycling rate, increase waste generation?
(b) Would smart cities and smart islands reduce energy consumption?
(c) Is smart technology making us smart (improve the quality of life) or dumb?
Building stocks and infrastructures are representing the largest material stock of industrial economies. In order to minimize the use of primary resources, greenhouse gas emissions as well as energy consumption for production of new materials, the “Urban Mining” strategy aims to recycle these urban stocks.
Smart City Vienna Strategy is based on the interplay of the three dimensions of: quality of life, resource conservation and innovation.
The Quality of Life addresses Vienna as the city with the highest quality of life and life satisfaction in the world; focusing on social inclusion in its policy design and administrative activities.
Resource Conservation foresees reduction of its local per capita greenhouse gas emissions by 50% by 2030, and by 85% by 2050 (compared to the baseline year of 2005); reduction its local per capita final energy consumption by 30% by 2030, and by 50% by 2050 (compared to the baseline year of 2005) and finally reducing material footprint of consumption per capita by 30% by 2030, and by 50% by 2050. By 2030 Vienna is an innovation leader; Vienna is Europe's digitalization capital.
For enabling of reduction of material footprint as well as to increase recycling rates detailed knowledge about the composition of building stocks is needed, as well as new methods for assessment, modelling and prediction of upcoming material flows in the future.
New business models to enable sustainable digital planning, construction and deconstruction workflows that facilitate the reuse and recycling of building materials and components along the lifecycle are needed.
How can digital technologies such as Building Information Modelling, GIS, blockchain and smart contracts enable a transparent, recycling-friendly assessment and tracking of building materials and building components along the lifecycle, thus minimizing and reducing emissions and waste?
What requirements must be met for a generation of publicly accessible digital urban mining cadaster as an instrument for a Smart City?
The smart building paradigm requires the understanding and incorporating indoor occupants’ needs and responses to the indoor visual and thermal environment conditions, which is not only for the provision and maintenance of individual occupants’ comfort but also the optimization and operation energy efficiency of building heating, cooling, and lighting systems. There are some widely recognized human indoor comfort prediction model and measurement methods, which has been well incorporated into the overall energy-efficient building design and building systems. However, the measures derived from these methods usually represent an “average” view of a group of users; in the smart building paradigm, differences in individual physiological responses and sensations, habitual conditions, and preferences over time and within different situations need to be taken into account. With the development of sensor technology and computing techniques, various real-time monitoring and predictive systems have been developed in recent years. Accordingly, by sensing, measuring, and predicting the dynamic personal factors, such as physiological features, behavior types, physical activity levels, user preference over time, and indoor positions, the advanced building control systems can adjust the specific components to enhancing occupants’ comfort in the micro-environmental conditions and offering great potential for energy savings.
The contemporary development is causing numerous crises, such as economic, health, environmental, social etc. Among these, the crisis in education is the most important for assuring long-term sustainable development of the human civilisation. Therefore, this contribution focuses on educational opportunities that address the urgent need to transform human settlements into smart settlements, cities, villages, islands etc.
Recent progress demonstrated that new technologies alone are not sufficient for this transformation. They need to be accompanied by a cultural transition, which is only possible by significant improvement of ICT competences among the general population. In this presentation, options for efficient improvement of the most relevant ICT competences are presented. They are analysed in terms of the expected advances in the ICT technologies, in particular by the fast 5G and 6G telecommunications and new applications of artificial intelligence that are based on the deep learning convolutional neural networks.
Recommendations for efficient implementation of the most relevant ICT competences in cities, villages, and islands are presented that enable these communities faster development into Smart Cites, Smart Villages, and Smart Islands.