Workshop 3: Urban Carbon Neutrality

Prof. Markus KRAFT

Director
Cambridge Centre for Advanced Research and Education, Singapore
Professor
Department of Chemical Engineering and Biotechnology, University of Cambridge, UK

Topic:
Big Data and Climate Change: How Cities Can Become More Resilient and Efficient

Date: 6 July 2023
Time: 14:00 – 14:30

Abstract:
This presentation focuses on the potential of big data and digitization to enhance the resilience of cities in the face of climate change and extreme weather events, while also supporting decarbonization efforts. It highlights the growing importance of integrating big data and digital technologies into city planning and management to improve climate risk assessments, early warning systems, and the monitoring and response to extreme weather events. The presentation also discusses how digital technologies can facilitate the deployment of renewable energy and energy-efficient building systems, thereby contributing to decarbonization. It concludes by emphasizing the need for policymakers, urban planners, and researchers to prioritize the use of big data and digital technologies in promoting climate resilience and decarbonization in cities.

Prof. Jianping WU

Professor
School of Civil Engineering, Tsinghua University, China

Topic:
Autonomous Driving and the Challengers to Future City

Date: 6 July 2023
Time: 14:30 – 15:00

Abstract:
With the rapid development of information technology, communication technology and artificial intelligence technology, autonomous driving and future transport are quickly approaching to us. However, from the first true autonomous driving car on the road to the era of fully autonomous driving, there will be a period of mixed traffic of autonomous driving vehicles and human driving vehicles. How to ensure that autonomous driving vehicles and human driving vehicles live in harmony during this period and build a safe and efficient future transport system is a new challenge for future traffic managers. This speech first describes the characteristics and prospects of autonomous driving and future transport, and then predicts the impacts and changes that autonomous driving and future transport will bring to future cities and future society, and finally, analyze and predict the challenges and opportunities in the development of autonomous driving and future transport.

Dr Xiaonan WANG

Associate Professor
Department of Chemical Engineering at Tsinghua University, China

Topic:
Harnessing the power of data via smart systems engineering towards an intelligent carbon-neutral future

Date: 6 July 2023
Time: 15:30 – 16:00

Abstract:
In light of the pressing environmental and climate change challenges, smart novel approaches are indispensable for sustainable development towards a net-zero future. Advances in artificial intelligence (AI), especially machine learning (ML), provide an enormous variety of smart tools for processing complex data generated from experimental and computational research, as well as industrial applications. AI and ML have substantially impacted the research and development norm of new materials and processes for energy and environment. This talk will first provide an overview and perspectives on ML applications to molecule/materials discovery and synthesis, as well as environmental management. Lab-scale low-carbon materials and processes research enabled by simulation and AI technologies driven by the integration of various cyber technologies with the physical system for rapid treatment through automation and connected entities. Active learning strategies are highlighted to incorporate ML in the high-throughput computational and/or experimental loop as an effective approach to accelerate the discovery of new materials with desired functionality such as CO2 capture and utilization. The capability of generative AI has also influenced many scientific domains by producing new data and understanding. Multi-scale AI and Optimization technologies help energy systems achieve low-carbon sustainable development, drawing on the intelligent digital twin to assist the planning of carbon peaking and carbon neutrality roadmaps. Ultimately, these smart technologies could enable accelerated materials discovery and process optimization, thereby facilitating improvement in energy efficiency, emission reduction, and eventually the realization of net-zero emission target.

Ir Prof. Lin LU

Professor
Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong

Topic:
Solar Reflectance Index (SRI) based functional nanomaterial solutions to energy smart building envelope

Date: 6 July 2023
Time: 16:00 – 16:30

Abstract:
The Solar Reflectance Index (SRI) is a measure of the solar reflectance and emissivity of materials that can be used as an indicator of how hot they are likely to become when solar radiation is incident on their surface. The lower the SRI, the hotter a material is likely to become in the sunshine. For our building skins and urban skins, we should choose materials with high SRI to reduce our building surface temperatures and building energy use for space cooling; to alleviate urban heat island effect; and to reduce our city’s temperature and the Earth’s temperatures. SRI based green building assessment criteria and cool roof scheme will be shared towards energy smart building envelopes. In addition, our advanced spectral selective nanomaterial solutions to cooling down our buildings via passive radiative cooling will be introduced.

Dr Yunting CHEN

Assistant Professor
The Eastern Institute for Advanced Study, China

Topic:
Scientific Machine Learning in Smart Energy

Date: 6 July 2023
Time: 16:30 – 17:00

Abstract:
Machine learning has been widely applied in the energy industry, but it still faces issues such as low model precision and robustness due to data scarcity and complex scenarios. This report explores the integration of knowledge in the energy industry with machine learning models. Knowledge embedding can break down the barriers between knowledge and data, thereby establishing machine learning models with physical common sense. Besides, human understanding of the world is always limited, and knowledge discovery can use machine learning to extract new knowledge from observations. By combining knowledge embedding and knowledge discovery, a closed loop of knowledge generation and utilization can be formed in the energy field, thus constructing smart energy models that are physically reasonable, mathematically accurate, and computationally stable and efficient. This report will discuss the progress in knowledge embedding and knowledge discovery in the field of smart energy, as well as potential applications in load forecasting and power forecasting.

Prof. Perry Pei-Ju YANG

Professor and Director of Eco Urban Lab
School of City & Regional Planning and School of Architecture, Georgia Institute of Technology, USA

Topic:
Incorporating Data Analytics into Urban Systems Design for Carbon Neutrality

Date: 7 July 2023
Time: 09:00 – 09:30

Abstract:
Future cities development is becoming data-driven in the context of data science, pervasive computing, internet of things (IoT) and urban automation. The emerging technologies are changing models of future urban living in the post-cyber space era. Ideas and methods for designing of zero carbon smart cities are urgently needed. They consist of smart homes, creative work places, interactive public spaces and critical infrastructure systems that are becoming situational, and have to be more adaptable and resilient for future changes. The talk introduces emerging models of smart cities development in Asian primate cities, including Tokyo, Singapore and Hong Kong. It explores future urban living in the face of global climate change, radical urban changes and impacts of emerging technologies to cities development. Asian primate cities are facing these challenges and are experimenting new models of smart cities living laboratory to reduce urban carbon emission to zero before 2050. Novel methods are to be developed to integrate city information system, creative design, systems engineering, policy and technological applications to offer solutions and strategies for addressing the above global challenges.

Prof. Fengqi YOU

Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering
Smith School of Chemical and Biomolecular Engineering, Energy Systems Engineering Cornell University, USA

Topic:
Deep Learning for Carbon Neutrality: AI Applications across

Date: 7 July 2023
Time: 09:30 – 10:00

Abstract:
Recent advances in machine learning, coupled with the rapid growth of computing power and scientific data infrastructures, led to increasing interest in applying deep learning-based methods for carbon neutrality. This presentation will briefly introduce our recent efforts in developing deep learning models and relevant AI tools in the quest for sustainability and carbon neutrality. Specifically, we will first present the results of several research projects, in collaboration with experimental materials scientists, to illustrate the applications of deep learning on: (a) Integrated design of metal-organic frameworks (MOFs) and adsorption processes via rapid, in-silico screening of MOFs for economically-efficient post-combustion CO2 capture and separation; (b) Understanding hierarchical protein assembly and developing soft sensors based on liquid crystal (LC) systems by analyzing complex spatiotemporal LC optical responses indicating the phase states of multi-protein assemblies formed at interfaces through high-throughput experiments; and (c) Inverse molecular design by developing expressive representations and effective data-driven models for quantitative structure-property relationships and quantum computing-assisted automated molecular structure optimization. The second half of the presentation will focus on the multi-scale applications of deep learning in materials discovery, polymer and protein structure optimization, plastic waste management, natural resource conservation, carbon-neutral energy transition, sustainable food production, reliable power supply, and climate adaptation. The presentation will conclude with our perspectives on integrating research and educational activities and catalyzing interdisciplinary collaborations to unlock unique opportunities toward a paradigm shift in AI for Science to support urban carbon neutrality.

Prof. Yingru ZHAO

Professor
College of Energy, Xiamen University
Vice Chairman
Fujian Electric Power Engineering Society

Topic:
Key technologies and applications for smart integrated energy systems

Date: 7 July 2023
Time: 10:30 – 11:00

Abstract:
Smart integrated energy is a cutting-edge solution that embodies new technological, modeling, and business paradigms aligned with the dual carbon goal. It is also a crucial driver for developing a modernized energy framework. Integrated energy offers vital features such as high renewable energy penetration and multi-energy flow coupling. However, due to the significant fluctuations in renewable energy output and load demand, the system displays complex dynamic stochastic patterns and uncertainties. The stable, efficient, and economical performance of an integrated energy system depends on system-level optimal design and performance regulation. This strategy calls for a scientific approach to system planning and design while considering temporal and complementary characteristics between loads, capacity, and energy storage devices under various geographical and climatic conditions. Moreover, the integrated energy system relies on a variety of intelligent techniques to coordinate different supply and conversion technologies and align their application with the demand side. In managing complex participant problems, trade-offs between multiple competing objectives must be taken into account. This dynamic and spatially distributed optimization design and performance regulation based on smart integrated energy presents an innovative approach to energy management. This talk aims to introduce the research status, development trends, and challenges confronting smart integrated energy. It will focus on key technologies such as load forecasting, system design, and optimization decision-making, among others.

Dr Haoran ZHANG

Assistant Professor
School of Urban Planning and Design, Peking University, China

Topic:
Modular Metacognitive Digital Twin Technologies for Greener Cities & Cleaner Mobility

Date: 7 July 2023
Time: 11:00 – 11:30

Abstract:
Digital twin technology can improve the level of refined and intelligent management of cities, and has wide applications in urban planning, epidemic and disaster prevention, smart logistics, and sustainability assessment. Cell phone mobile data, as a more accessible fine-grained data set at the city level, has high mining value. However, the seemingly massive and huge cell phone mobile data actually contains serious problems such as sample scarcity, sampling bias, and heterogeneous errors. Then, how to simulate the real "big world" based on the "small world" constructed by the rough cell phone data and guided by the physical constraints of urban population movement behavior becomes one of the research bases of the digital twin city. This talk will focus on our recently built small world AI model - cell phone mobile data processing and analysis system, and its application to smart stations, smart energy and urban sustainability indicators assessment.

Dr Siqi BU

Associate Professor and Associate Head
Department of Electrical Engineering,
The Hong Kong Polytechnic University, Hong Kong

Topic:
Secure Operation of A Low-Carbon Sustainable Urban Grid

Date: 7 July 2023
Time: 11:30 – 12:00

Abstract:
Sustainability and security are sometimes two conflicting factors in the low-carbon urban grid operation, especially when considering the impact of massive distributed energy resources (DERs). Considering the fact that power industry is one of the main industrial sectors that should be responsible for carbon reductions in an urban city, this talk will firstly introduce the developing trend and growing risks during the low-carbon transition of so-called urban active distribution networks (ADNs), featured by the large-scale integration of distributed renewable energy sources and smart loads. To deal with these emerging challenges resulted from the decarbonization, the talk will then move on to some latest developed innovative techniques and tools to effectively accommodate and utilize the increasing DERs and mitigate the associated operational risks in ADNs, in order to enable the secure and economic operation of low-carbon sustainable urban grid for timely achieving of urban carbon neutrality.