Short Abstract :
Due to the evident climate change and environmental pressures the future power/energy systems will have to operate, sooner rather than later, in a net-zero environment. This will manifest in a mix of wide range of electricity generation, storage and demand technologies (increasingly power electronics interfaced); blurred boundaries between transmission and distribution system; significantly higher reliance on the use of legacy and measurement data including global signals for system identification, characterization and control and Information and Communication Technology embedded within the power system network and its components. The key characteristics of such a complex system, would certainly be proliferation of power electronic devices in different shapes and forms and for different purposes, increased uncertainties in system operation and parameters and much larger reliance on the use of measurement and other data collected. This presentation will first briefly introduce some of the key characteristics of future net-zero power systems and summarize the key challenges associated with operation, modelling and control of such systems. Following this examples of the latest research results in the areas of probabilistic stability studies of uncertain systems, data analytics, risk assessment and complex system analysis, all constituent parts of operation and control of net-zero power systems, will be discussed.
Short Bio :
Professor Milanović is Head of Department of Electrical and Electronic Engineering at The University of Manchester, UK, Visiting Professor at the University of Novi Sad and the University of Belgrade, Serbia and Honorary Professor at the University. Of Queensland, Australia. He was chairman of 5 international conferences, member of 9 (convenor of 3) past IEEE/CIGRE/CIRED WG, participated in or lead numerous research projects with total value of over £80 million, published over 600 research papers and reports, gave over 30 key-note speeches at international conferences and presented over 150 courses/tutorials and lectures to industry and academia around the world. He is a Chartered Engineer in the UK, Foreign member of the Serbian Academy of Engineering Sciences, Fellow of the IET, Fellow of the IEEE, Distinguished IEEE PES Lecturer, member of the IEEE PES Industry Technical Support Leadership Committee, member of the IEEE PES Long Range Planning Committee, member of IEEE Fellows Committee and Editor-in-Chief of IEEE Transactions on Power Systems. He was a member of the IEEE PES Governing Board as Regional Representative for Europe, Middle East and Africa for six years, member and vice-chair of IEEE PES Fellows Evaluation Committee and member and Chair of the IEEE Herman Halperin Transmission and Distribution Award Committee.
Short Abstract :
Organizations across the globe are devising novel approaches to strive for carbon neutrality. Global institutions have manifested the critical need to develop reasonable strategies in every sector to mitigate the impending issues of excessive anthropogenic carbon emission and, in consequence, climate change. World-leading economies have initiated significant steps by developing zero-carbon emission policies to monitor the escalating carbon emissions to curb global warming. The clothing industry features a substantial carbon footprint while causing environmental pollution. Based on transition management theory, this presentation aims to explore and evaluate the critical determinants that can assist in pursuing carbon neutrality in the clothing industry. The presentation will cover the following aspects.
A decision support system comprising an integrated voting analytical hierarchy process (VAHP) and Bayesian network (BN) method.
Identification of critical determinants for carbon neutrality (CDs-CN) and prioritising them using the VAHP method.
Development of a tool to predict the carbon neutrality index (CNI) using a BN. The findings reveal that professional expertise, laws and certifications, technological acceptance, availability of decarbonizing methods, and adequate carbon offsetting are the essential CDs-CN. This presentation extends the existing knowledge on integrating MCDM-ML techniques to address predictive modelling-based problems involving complex structures.