Differentially Private Smart Meter Data Markets: An Interdisciplinary Approach

Lead Research Organisation: Imperial College London
Department Name: Electrical and Electronic Engineering


Full title: Agent-based simulation approach to the provision of ancillary service by demand response and distributed storage and generation assets in the future low carbon system

This project aims to investigate one of the most pertinent challenges facing electricity markets today. The push for rapid decarbonisation of the electricity sector is leading to increased amounts of intermittent renewable generation such as wind and solar within the power system increasing system integration costs. The need to ensure the instantaneous matching of supply and demand, as well as system security through reserve margins requires grid system operators to contract ancillary services from market participants. The decreasing costs of Battery Energy Storage (BES), developments in smart metering and Demand Side Management (DSM) provide opportunities for distributed, small-scale generation and storage assets to participate in the ancillary services market.
Existing studies have focused on cost-optimal and automated dispatching solutions, using production-cost models which assume market participants typically make rational choices, respond to pricing signals, have perfect foresight, and operate in the absence of market power. Such an approach, however, does not take into account the fact that market participants exhibit heterogeneous behaviour. In particular, distributed DSM and BES assets exhibit diverse attitudes and behavioural intentions that are often ignored or only assessed qualitatively. The project proposes the use of an agent-based approach to account for behavioural difference and to allow for the formulation of appropriate incentive structures and provide insight into what is required to achieve reliable service from distributed assets.
By integrating an interdisciplinary framework, the research attempts to capture the effects of different socio-psychological-economic factors that influence agent behaviours in a distributed network with the ultimate aim of translating these findings into practical and actionable policy recommendations.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000703/1 30/09/2017 29/09/2027
2113082 Studentship ES/P000703/1 01/01/2019 30/03/2022 Saurab Chhachhi