Keynote Speakers

Abstract

The increasing penetration of renewable energy sources into electrical power networks has introduced a number of technical and economic problems arising principally from the variability of energy production, the diversity of generating technologies, and the requirements of maintaining a satisfactory balance between supply and demand. The combination of renewable generation with electrical and hydrogen energy storage offers considerable possibilities for improving system operation and reducing dependence upon conventional generating resources. The determination of suitable system configurations and operating conditions, however, requires the simultaneous consideration of technical performance, investment expenditure, operating costs, and environmental effects.

This study considers the techno-economic modeling and multi-objective optimization of an integrated energy system comprising solar and wind generation, electrical energy storage, hydrogen production by electrolysis, hydrogen storage, and fuel-cell generation. A mathematical representation of the principal system components is employed together with an intelligent control arrangement to examine their combined operation under different technical and economic conditions. The optimization procedure considers operating costs and carbon dioxide emissions as principal objectives, while accounting for the characteristics and operating constraints of the individual energy resources.

The application of the proposed approach to the Iowa 240-bus power system in the United States indicates the potential advantages of coordinated renewable energy integration. The reported results show annual savings of $126,147.8 and a reduction of 951,035.6 kg in carbon dioxide emissions relative to the base case, corresponding to reductions of 10.3% in annual costs and 100.5% in annual emissions. These results demonstrate the importance of considering the interactions among renewable generation, energy storage, and conversion technologies when evaluating alternative energy system configurations.

The study further discusses the practical significance of mathematical modeling, intelligent control, and multi-objective optimization in the planning and operation of integrated energy infrastructures. Particular attention is given to the technical and economic considerations governing the selection and coordination of different energy resources and their possible contribution to the development of low-carbon power systems.

Abstract

Sustainability and sustainable development are important goals for human and societal activity. Energy sustainability is of great importance to any activities and plans for overall sustainable development, and the achievement of sustainability. This is particularly important given the pervasiveness of energy use throughout almost all aspects of societies and the lives of people and the importance of energy in economic development of societies and the living standards attained by people, in addition to the significant impacts that energy processes and systems have on the environment and the ecosystems within them.

Many factors that need to be considered and appropriately addressed in moving or shifting towards energy sustainability are examined in this talk. These include appropriate selection of energy resources bearing in mind sustainability criteria, facilitation of the use of sustainable energy resources particularly through the use of appropriate energy carriers, enhancement of the efficiency of energy-related processes, and a holistic adoption of environmental stewardship in energy activities. In addition, other key sustainability measures are addressed, such as economics, equity, land use, lifestyle, sociopolitical factors and population, and examples of energy sustainability measures are described.

Finally, the talk focuses on the important contributions that buildings and communities can make towards achieving energy sustainability. This is important given that, in most countries, buildings are responsible for 30-40% of national energy usage.

Abstract

The increasing application of artificial intelligence (AI) in mobility and transport systems raises important questions concerning the representation of different population groups and the extent to which data-driven decisions reflect their mobility needs. While AI-based models are increasingly employed to improve transport efficiency, accessibility, safety, and sustainability, their outcomes depend substantially upon the quality and composition of the underlying datasets. In particular, imbalances in demographic representation may introduce systematic biases that affect how mobility services are planned, evaluated, and delivered.

This keynote examines the relationship between data representation, algorithmic fairness, and inclusive mobility planning, with particular emphasis on gender-related disparities in transport and safety datasets. Drawing upon open mobility data, sectoral statistics, and AI-supported scenario modeling, the presentation considers how differences in gender representation can influence accessibility assessments, safety evaluations, and transport optimization outcomes. Attention is given to the comparison of balanced and empirically observed data distributions, as well as to the implications of these differences for the reliability and fairness of AI-based mobility models.

The discussion further addresses the practical challenges of identifying and mitigating demographic bias in intelligent transport systems without compromising operational efficiency. By examining the relationship between data balance, model performance, and the mobility requirements of different user groups, the keynote considers the conditions under which AI-supported transport planning may contribute to safer, more equitable, and sustainable mobility systems. Particular emphasis is placed on the responsibility of researchers, transport planners, and technology developers to ensure that advances in mobility intelligence serve the diverse populations for whom these systems are intended.

Abstract

The design of a solar photovoltaic (PV) system involves a series of technical and engineering considerations, each of which has a direct bearing upon the performance, reliability, and economy of the installation. A satisfactory design requires not only an understanding of the operating characteristics of photovoltaic modules and associated equipment, but also a systematic assessment of the electrical load, local solar radiation, environmental conditions, and requirements of the proposed installation.

This keynote addresses the principal stages in the engineering design of solar PV systems, with particular attention to the determination of energy requirements, estimation of available solar resources, selection and sizing of PV modules and inverters, arrangement of the PV array, and calculation of the principal electrical parameters. Consideration is also given to system losses, protection requirements, and the estimation of electrical energy production under practical operating conditions.

The presentation follows the principal engineering calculations and design decisions involved in a representative grid-connected PV installation, illustrating the relationship between theoretical considerations and their application in practice. Particular emphasis is placed upon the assumptions, technical constraints, and engineering judgments that must be considered in arriving at a suitable system configuration. The discussion is intended to provide an integrated account of the essential design procedure within the scope of a conventional solar PV installation.