Household electricity demand, the intrinsic flexibility index and UK wholesale electricity market prices

Abstract

During peak electricity demand periods, prices in wholesale markets can be up to nine times higher than during off-peak periods. This is because if a vast number of users is consuming electricity at the same time, power plants with higher greenhouse gas emissions and higher system costs are typically activated. In the UK, the residential sector is responsible for about one third of overall electricity demand and up to 60% of peak demand. This paper presents an analysis of the 2014–2015 Office for National Statistics National Time Use Survey with a view to derive an intrinsic flexibility index based on timing of residential electricity demand. It analyses how the intrinsic flexibility varies compared with wholesale electricity market prices. Findings show that spot prices and intrinsic flexibility to shift activities vary harmoniously throughout the day. Reflections are also drawn on the application of this research to work on demand side flexibility.

A bilevel model for voluntary demand-side flexibility in distribution grids

“…The contribution of residential demand to the system demand peak is important. In Europe, it contributes about 60% of the system peak (Torriti, 2020), while in some parts of the US, South Australia and New Zealand, it accounts for around 50% ( (Gyamfi et al, 2013) and (EDF, 2013)). The contribution of the residential sector to the overall electricity demand is less important than its contribution to the peak.…”

“…The contribution of the residential sector to the overall electricity demand is less important than its contribution to the peak. In Europe, it accounts for about one-third of the electricity demand (Torriti, 2020). For the critical days, we selected load profiles of residential consumers with an evening peak of ~7 kW, while the day peak is ~6 kW.…”

Scalable multi-agent reinforcement learning for distributed control of residential energy flexibility

“…Residential energy has substantial such flexibility potential, particularly as private transport and heat provision are electrified. For example, in the UK, the residential sector already represents about one third of overall electricity demand and up to 60% of peak demand, when the value of flexibility is highest [1].…”

“…Using a multi-agent actor-critic framework that learns decentralised policies with a centralised but factored critic addresses the pitfalls of both the poor coordination performance of independent learners and the intractability at scale of optimisations or centralised critic estimation. To enhance the performance of DER coordination, we further improve the centralised but factored critic methodology by incorporating two techniques: convolutional neural networks 1 For the remainder of this paper, we will use "FACMAC" and "centralised but factored critic approach" interchangeably.…”

Demand response with heat pumps: Practical implementation of three different control options

“…For example, in Great Britain widespread adoption of heat pumps and other electric heaters is estimated to increase electricity demand by up to 65% and peak demand by up to 115%. 7 It also creates large seasonal variations in electricity demand 8 and exacerbates existing daily variations 9 which are not necessarily correlated with supply of renewable electricity. Furthermore, transmission and distribution grids will require increased capacity.…”