讲座题目：人工智能技术在二氧化碳减排领域的应用

报 告 人：Markus Kraft

时 　 间：2020年1月13日(周一)9:30-11:30

地 　 点：中关村校区3号教学楼146

主办单位：研究生院、机电学院

报名方式：登录北京理工大学微信企业号---第二课堂---课程报名中选择“【百家大讲堂】第315期：人工智能技术在二氧化碳减排领域的应用”

【主讲人简介】

  Markus Kraft教授是剑桥化学工程与生物技术系教授，新加坡剑桥CREATE研究中心主任，CARES研究计划中的“化学技术CO2减排剑桥中心”的首席研究员。Markus Kraft教授于1992年在Kaiserslautern大学获得了应用数学学士学位，并于1997年在该大学获得了了化学博士学位。之后，在卡尔斯鲁大学和柏林的维尔斯特拉斯应用分析与随机研究所工作。1999年，成为剑桥大学化学工程系的讲师。2012年，在剑桥大学获得了名誉博士学位。他的研究主要是致力于对汽车，电力和化学工业中的二氧化碳减排技术的计算建模和优化处理。

Prof Markus Kraft is a Fellow of Churchill College Cambridge and Professor in the Department of Chemical Engineering and Biotechnology. He is the director of CARES, the Singapore-Cambridge CREATE Research Centre, and Principle Investigator of C4T the “Cambridge Centre for Carbon Reduction in Chemical Technology”, which is a CARES research programme. Professor Kraft obtained the academic degree 'Diplom Technomathematiker' at the University of Kaiserslautern in 1992 and completed his Doctor rerum naturalium in Chemistry at the same University in 1997. Subsequently, he worked at the University of Karlsruhe and the Weierstrass Institute for Applied Analysis and Stochastics in Berlin. In 1999 he became a lecturer in the Department of Chemical Engineering, University of Cambridge. In 2012 he obtained a ScD form the same University. He has a strong interest in the area of computational modelling and optimisation targeted towards developing CO2 abatement and emissions reduction technologies for the automotive, power and chemical industries.

【讲座信息】

  由温室气体所引起的全球变暖在近些年来引起了广泛的关注。在不久的将来，能源的供应方式将进行重大的改进，用以降低甚至阻止大气温度的升高和随之而来的负面后果。在本次演讲中，Kraft 教授将重点介绍基于人工智能（AI）的网络物理系统和知识图谱在CO2减排领域的应用。目前，大数据，机器学习和互联网等数字技术正受到越来越多的关注，正是因为它们可以在有限的经济投入下帮助实现CO2减排。基于这些先进的数字技术，即形成所谓的网络物理系统（CPS），可提供进一步的协同效应，从而提高能源供应和工业生产的效率，进而优化其经济可行性和环境友好性。本次演讲将会评估CPS中数字技术对能源系统减排的即时作用以及潜在的影响。此外，当CPS与人工智能（AI）结合使用时，减排技术可能会以不可预见的速度发展，但同时也伴随着难以预测的潜在风险。Kraft教授团队目前正在开发的网络物理系统称为J-Park Simulator（JPS），它是http://www.theworldavatar.com/项目的一部分。JPS由一个包含域本体的IRI网络，知识库和不同类型代理组成。它的一个重要的应用是生态工业园区的建模和优化，这包括了电网，各种物理网络（例如，废热网络）以及每个工业过程的详细模型。在本次演讲中，Kraft教授将解释JPS的工作原理并给出几个实际示例。

Global warming caused by greenhouse gases have caused great concern for a number of reasons. It is clear that drastic changes have to be implemented in the near future to reduce or stop the increase of average temperature and the many negative consequences that go with it. In my talk I shall concentrate on AI-based Cyberphysical systems and knowledge graphs.  The decarbonisation of energy provision is key to managing global greenhouse gas emissions and hence mitigating climate change. Digital technologies such as big data, machine learning, and the Internet of Things are receiving more and more attention as they can aid the decarbonisation process while requiring limited investments. The orchestration of these novel technologies, so-called cyber-physical systems (CPS), provides further, synergetic effects that increase efficiency of energy provision and industrial production, thereby optimising economic feasibility and environmental impact. This comprehensive review article assesses the current as well as the potential impact of digital technologies within CPS on the decarbonisation of energy systems. Ad-hoc calculation for selected applications of CPS and its subsystems estimates not only the economic impact but also the emission reduction potential. This assessment clearly shows that digitalisation of energy systems using CPS completely alters the marginal abatement cost curve (MACC) and creates novel pathways for the transition to a low-carbon energy system. Moreover, the assessment concludes that when CPS are combined with artificial intelligence (AI), decarbonisation could potentially progress at an unforeseeable pace while introducing unpredictable and potentially existential risks. The cyber-physical system we are currently developing is called J-Park Simulator (JPS) which is the signature project in the C4T programme of CARES at the University of Cambridge and part of the http://www.theworldavatar.com/ project.  JPS consists of a network of IRIs comprising domain ontologies, a knowledge base and different types of agents. One important application is the modelling and optimisation of eco-industrial parks. This includes the electrical grid, various networks of materials, for example, waste heat network along with a detailed model of each industrial process. In my talk I shall explain how JPS works and show a couple of examples.