Intelligent Energy Systems
Meeting the challenge of cutting greenhouse-gas emissions and ensuring energy security requires radical changes in the ways in which energy is generated, distributed and consumed.
Central to this change is the vision of the smart grid – anelectricity network in which information flows freely between consumers andsuppliers, and demand adapts in real-time in response to the continuously changing supply from intermittent renewable sources.
The decentralized nature of the smart grid, and the autonomous intelligent behaviour expected of it, is increasingly leading power-systemsengineers to turn to novel information- and communication-technology approaches to understand how to build and control this new grid. In particular, the field of multi-agent systems offers a rich set of techniques, algorithms and methodologies for building distributed systems in which desirable system-wide properties can be assured, despite the autonomous (and perhaps self-interested) actions of the component parts (here individual homes and businesses making their own decisions about energy generation and consumption).
Researchers within AIC have been at the forefront of the application of multi-agent systems in future energy systems such as the smart grid. Work to date has addressed areas as diverse as the coordination of energy storage, the pricing of electric vehicle charging, the formation of virtual power plants, and the development of personal energy assistants that can advise on and automate home energy use.
Intelligent infrastructure
We increasingly rely on an interdependent network of complementary, interacting, infrastructure systems: transport, energy, water, waste, ICT, and even governmental, health care and emergency services. In the UK, and in advanced economies globally, these systems face serious challenges. There is an urgent need to reduce carbon emissions from infrastructure systems, to respond to future demographic, social and lifestyle changes and to improve resilience.
Acheiving this will require interdsiciplinary collaboration and a complex systems perspective. Recent reports from, e.g., the Institute for Public Policy Research, the Institution of Civil Engineers, the Council for Science and Technology, and the Cabinet Office agree that achieving and sustaining resilience is a key challenge facing the UK’s infrastructure systems. Examples of stresses and shocks range from climate change and demograhpic change, to systemic failure and terrorist attack. The complex, disparate and interconnected nature of the UK’s infrastructure is a key concern. Our infrastructure systems are highly fragmented both in terms of their governance and in terms of the number of agencies charged with achieving and maintaining resilience, which range from national government to local services and even community groups and local resilience forums. Moreover, the cross-sector interactions amongst different technological and techno-social systems within national infrastructure systems are not well understood. AIC research in modelling and managing infrastrcture is working towards a better understanding of the resilience implications of our current and future infrastructural organisation; and vehicles for effectively conveying this understanding to the full range of relevant stakeholders.
Socio-economic systems
We are surrounded by and embedded in social systems that were not planned or designed but rather grew out of historical contingency. For example, consider the global trade network, global financial markets, systems of national government, education systems, and demographic phenomena such as the family, the neighbourhood, the town, and the city. In some cases we are confident that our social institutions are both well-adapted and worth preserving, e.g., the system of trial by jury, or the separation of powers between legislative, judicial, and executive branches of government. In other cases (e.g., global trade imbalances and wealth inequality) most would agree that the current state of affairs is unjust or inefficient, but the difficulty is in finding a feasible path to a better arrangement. Pervasive social systems are not easily "switched off" while a new and improved model is installed.
The AIC group uses agent-based computing and ideas from economics in order to build robust multi-agent systems in software and hardware. The same methods (agent-based modelling, optimization, mechanism design) can be applied to problematic social systems with a view to making clear the potential inefficiencies in the current arrangement, and proposing better ways of doing things in the future.
Examples of this work include the Care Life Cycle project, in which agent-based modelling researchers from the AIC group are working with social scientists in order to model the provision of formal and informal social care in the UK, a particularly pertinent issue given the demographic shift towards a more elderly population. A second strand of work includes models that highlight inefficiency and suggest reform in the institutions of science itself (e.g., funding, peer review, training, etc.).