Multi-scale Modelling to Maximise Demand Side Management (Application to Part 2 of the Call)

Project: Research

Description

Modern energy systems are complex technical, social and economic endeavours formed through the assembly of a broad set of elements and shaped by the actions of many multiple actors including consumers, suppliers and regulators. While some gains can be achieved by optimising parts of these systems, significant reduction in energy demand is a major challenge requiring changes in behaviour from all the actors involved. In this proposal we wish to exploit the ability of digital technologies to monitor, model and represent the operation and effects of energy demand to promote changes in these systems. This is often realised through a set of actions and measures, commonly known as demand side management (DSM). Current approaches to DSM and reduction of energy demand, however, are often viewed entirely from the consumer's perspective, concentrating mostly on the importance of behavioural changes and the role of energy displays (or smart meters ) as main drivers of these changes. This emphasises only one part of modern and increasingly complex energy systems, which actually need to be understood in their entirety to ensure that changes will have both significant and sustainable impact. Accordingly, this proposal adopts an end-to-end approach to exploit digital technology to understand the overall energy supply system (from generation to transmission, distribution and utilisation), in which devised changes are targeted at the points of maximum impact and all involved system elements are fully optimised to reap the benefits of these changes. The ultimate aim of our research is to answer how the significant potential benefits of DSM can be maximised through the provision of a unified, versatile and affordable digital infrastructure that allows us to reason across a whole energy system and supports new ways to exchange information between dynamic multiscale DSM models. The expected outcome is access to, and presentation of, not just quantitative information (e.g. the amount of modified active/reactive power demands), but also qualitative information (e.g. what are the actual load mixes and load sectors responsible for the changes in demand and what are their definite effects) to all involved stakeholders. In particular, we wish to link the use of modern digital technologies, capable of impacting the behaviour of the consumers, with the ability to optimally respond to the resulting changes in energy demand. The project team brings together researchers with a background in ubiquitous computing, complex systems modelling and user centred development to work with researcher focusing of real world energy systems and energy economics. We will adopt a user driven approach to the design and development of a series of computational models and digital technologies working closely with consumers, energy supply companies and government bodies to explore a set of exciting state-of-the-art innovations based on low-cost sensing and display technologies. The project team has strong connections with key industrial, public sector and academic groups in UK and internationally, and these will be used to ensure that the proposed research will have maximum impact. Free access to any developed system to promote change, and a publicly accessible web site will be maintained for the dissemination of the results. We intend to make any software artefacts and device designs available via open source distribution through the Horizon DE Hub. We will build upon our existing public dissemination work to emphasise issues of ethics and societal impact as important features of this work.

Key findings

"This provided the first system-wide analysis of the likely economic and environmental impact of the roll out of smart meters, generating an increase in efficiency in electricity consumption. While higher substitution among fuels in household energy consumption increases the rebound, and the risk of backfire, it may also reduce overall emissions.

DECC's projections of offshore wind capacity are conducted in a model that neglects wider economy-energy-environment interaction. In the other paper we establish that DECC's learning rate assumptions about offshore wind technology is in itself insufficient to ensure the targets are met. However, despite the economic expansion resulting from technological improvements in the offshore wind electricity generating sector, overall emissions fall, as the electricity mix becomes less fossil-fuel intensive."
StatusFinished
Effective start/end date1/01/1131/12/13

Funding

  • EPSRC (Engineering and Physical Sciences Research Council): £105,923.06

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Smart meters
Economics
Electricity
Display devices
Ubiquitous computing
Reactive power
Fossil fuels
Environmental impact
Demand side management
Large scale systems
Websites
Substitution reactions
Energy utilization
Innovation
Costs
Industry