Domestic demand response in Great Britain: An examination of flexibility markets and adoption

  • Timothy Capper

Student thesis: Phd

Abstract

The United Kingdom's government has committed to reaching net zero greenhouse gas emissions by 2050, and to meeting carbon budgets on the way, with the aim of helping to limit the average global temperature rise to 1.5 degrees C. To achieve this, the Climate Change Committee projects that electricity generation must become gross zero carbon by 2035. Zero carbon electricity generation means that the balancing services currently provided by gas turbines must be replaced. Carbon budgets also require the electrification of domestic heating and light transportation by 2050, leading to a potential three-fold increase in electricity demand. Demand response has been proposed as one way of replacing some of these balancing services, and shifting demand away from peak times to reduce the amount of network reinforcement required to meet an increasing demand. The domestic loads, such as heat pumps and electric vehicles, which might provide demand response have other primary purposes. The owners of these loads will not necessarily choose to adopt demand response if it is not financially beneficial to them. This thesis presents three pieces of research which examine the financial incentives provided by the markets for flexibility in Great Britain, and other factors which might lead to the adoption or rejection of demand response. This thesis first uses a Monte Carlo simulation to show that the British balancing mechanism does not provide a financial incentive for participants to reduce their energy imbalance over time, by investing in storage or providing demand response. An amended imbalance charge is proposed which does provide such an incentive. This thesis then goes on to use expert interviews to examine the policy, regulatory and market design issues which might lead to domestic demand response being adopted or rejected. The results of these interviews show the importance of having consistent requirements for participation in different flexibility markets, the requirement for regulation of flexibility markets, and the importance of cost-reflective pricing. The final piece of work in this thesis uses a mixed integer linear programming model to explore the interaction between different flexibility markets in terms of the incentives they provide to heat pumps and electric vehicles. This final piece of research also examines the effect of different set points and specifications on the level of flexibility that heat pumps and electric vehicles can provide. This thesis finds that the flexibility markets in Great Britain today are not well designed for the participation of domestic demand response. The balancing mechanism does not provide an enduring financial incentive for energy suppliers and other electricity market participants to take measures to reduce their energy imbalances. An enduring penalty on energy imbalances would be a strong incentive for energy suppliers to build up a demand response portfolio amongst the loads they settle. Households directly exposed to distribution network operator flexibility markets and the balancing mechanism do not provide additional flexibility above and beyond that provided when only exposed to time-of-use tariffs. Although stacking multiple flexibility markets is valuable to the household, it does not provide an additional benefit to the electricity system. Finally, this thesis provides some tentative results about how flexibility markets might be better designed to accommodate domestic flexibility. These changes include a redesign of the imbalance charge calculation and making the energy price more cost reflective.
Date of Award31 Dec 2023
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorMaria Sharmina (Supervisor) & Jaise Kuriakose (Supervisor)

Keywords

  • renewable energy
  • electricity
  • balancing mechanism
  • diffusion of innovation
  • mixed integer linear programming
  • semi structured interview
  • monte carlo simulation
  • demand response

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