BSC insight: How Covid-19 impacts Load Profiles

There are two different types of data that the Balancing and Settlement Code (BSC) requires for electricity Settlement; Half Hourly and Non Half Hourly. Electricity Settlement happens in Half Hourly periods, so Elexon uses the profiling process to calculate Half Hourly data from Non Half Hourly meters. In this Insight article, Mehdi Jafari discusses the Group Average Demand data used in the profiling process and the way it has been impacted by the COVID-19 pandemic.

Converting Non Half Hourly data into Half Hourly data

Supplier Volume Allocation (SVA) energy consumption data is from customers who are connected to Distribution Networks. In 2020, 52.2% of Supplier Volume Allocation (SVA) energy consumption came from Non Half Hourly customers, whose meters are read no more than a few times a year. To convert Non Half Hourly data into Half Hourly data for the Settlement, Elexon use Profile Coefficients to calculate Half Hourly data from meter reads. Profile Coefficients are calculated using Load Profiles. A Load Profile represents the pattern of electricity usage by day and by year for the average customer in each one of the eight Profile Classes. Load Profiles enable competition in electricity supply market.

What is a Profile Class?

Electricity consumers are categorised under eight Profile Classes, four of which correspond to Non Half Hourly customers. The four that correspond to Non Half Hourly customers are:

  • Profile Class 1 Domestic Unrestricted Customers (Single Rate)
  • Profile Class 2 Domestic Economy 7 Customers (Two Rate)
  • Profile Class 3 Non-Domestic Unrestricted Customers (Single Rate)
  • Profile Class 4 Non-Domestic Economy 7 Customers (Two Rate)

Load Profile data is created by recording and analysing Half Hourly demand data from a representative sample of customers, for each of the four Profile Classes.  Following the implementation of BSC Modification P223, Suppliers are required to provide Sample Participants data from customers within their portfolios to the Profile Administrator (PrA) who create Load Profiles.

Group Average Demand and Regression Analysis

For each Profile Class, the average demand across all samples per a Settlement Period give Group Average Demand (GAD) data which is used in a regression analysis as the dependent variable. In the regression analysis, the aim is to calculate the regression coefficients which describe the relationship between a dependent variable and one or more independent variables. The relationship between the GAD and the regression variables can then be described using regression coefficients. In the profiling process, the dependent variable is GAD and the independent variables are temperature and day type. The regression coefficients describe the relationship between GAD and regression variables which are Noon Effective Temperature (NET), Sunset variables, and day type variables.

COVID-19 and Profile Classes’ Group Average Demand

Elexon previously published two Insight articles on the impact of COVID-19 pandemic on electricity demand in  2020 where we reported an average of 17% reduction in demand during lockdown weeks compared to the weeks before lockdown. As we have now been in lockdown for a year, we are able to review the effects of lockdown on Non Half Hourly Profile Classes.

The Government advised working from home on 16 March 2020 and then announced the first national lockdown on 23 March 2020. As more people started remote working, Profile Class 1 and 2, domestic customers, began to see an increase in the average GAD compared to the same time periods in previous years. The graph above shows the average of GAD per Profile Class over the last four years per Settlement Period.

Domestic Customers

Profile Class 1 and 2, which represent domestic customers, experienced an increase in demand during the periods where GB was in lockdown. On average, 2019 was 1.88% colder than 2018. This could be part of the reason why the GAD increased by around 2% for Profile Class 1 between 2018 and 2019.

In GB, typically when there is as increase in temperature, electricity demand falls. In 2020 as a whole,  temperature was on average higher than 2019; however, there was an increase of around 3.6% in the average GAD for domestic customers. This could be attributed, in part, to the restrictions put in place to tackle the spread of COVID-19, which led to a large number of people working from home or being placed on furlough.

Impacts of the first lockdown

In March 2020, when many businesses started working from home and most schools closed, the GAD average over sample customer in Profile Class 1 increased by 12.54%. The increase is, as expected, higher over week days with 13.94% and lower over weekends with 9.66%.

In April 2020, during the first national lockdown, the Profile Class 1 experienced the highest increase 13.94% in the GAD average compared to April 2019. This was resulted from 15% increase in GAD for week days and 11% for weekends.

Impacts of easing COVID-19 restrictions

The restrictions put in place by the government during the first lockdown, began to ease in late May and early June 2020. However, the GAD average in Profile Class 1 remained more than 10% above the 2019 level until July and August when it dropped respectively to 7.61% and 5.61% above the July and August 2019 GAD average. In September 2020 the GAD average dropped for the first time since January 2020 to below 2019 levels, indicating that more people were returning to work; less domestic energy consumption.

Working vs non working hours

A breakdown of GAD for Profile Class 1 over working hours (9am to 6pm) when most home office devices work for period between March and September 2020 shows a GAD average 16.22% higher than 2019 levels. This is only 7.70% for non-working hours.

Profile Class 2

Similar to Profile Class 1, the average GAD for Domestic customers in Profile Class 2 was higher in 2020 than 2019 after first lockdown started in March. However unlike Profile Class 1, it remained lower than in 2019 during March and April. In May the GAD average for Profile Class 2 exceeded 2019 levels, with August witnessing the highest increase with 12.47%.

Non-Domestic Profiles

Profile Class 3 and 4 represent Non-Domestic Customers below 100 kW Maximum Demand. They are small and medium businesses whose metering systems are Non Half Hourly and are read no more than a few times a year. COVID-19 meant that these customers experienced the opposite effects of domestic customers. Almost all shops were closed from 16th March 2020 to 15th June and restaurants to 4th July. The GAD average decreased by 14% for Profile Class 3 and 10% for Profile Class 4 in 2020 compared to 2019, representing the reduction in these businesses’ activities. This decrease was higher over weekdays with over 15% for Profile Class 3 and 11% for Profile Class 4, and lower over weekends with around 10% for Profile Class 3 and 7% for Profile Class 4.

In April 2020, during the first month of the first national lockdown, Non-Domestic customers experienced the highest fall in their GAD from 2019 with 32% reduction in GAD for Profile Class 3 and 38% for Profile Class 4. This is around 49% over working hours for Profile Class 3 and 53% for Profile Class 4 which shows how severe businesses suffered from the pandemic.

What are the impacts of the changes in GAD on the profiling process

The Profiling Administrator (PrA) use GAD along with temperature, sunset, and day type variables to calculate regression coefficients; i.e. the relationship between GAD and temperature, sunset, and day type variable. The regression coefficients are then used to calculate profile coefficients for the next year. Half Hourly data is calculated in each Settlement Period from Non Half Hourly meter reads by multiplying the Profile Coefficients by customer’s estimated annual consumption which is either Annualised Advance or Estimated Annual Consumption. The standard practice is calculating the profiling data using a 3-year pooling process, e.g. using 2017, 2018, and 2019 data to estimate 2020.

The pandemic restrictions impacted the GAD data dramatically. As there were uncertainties as to whether the pandemic will be over soon or will extend into the current year, the PrA presented their analysis to Profiling Expert Group (PEG) in January 2021 recommending two methodologies. One based on pooled data over three years (2018, 2019 and 2020), and the other based on a single year’s data (2020). This allowed the PEG to make a later decision on which methodology to use closer to the deadline, given the ever changing COVID-19/lockdown situation.

Profile Coefficients

As an example, the graphs below show the profile coefficients for Profile Class 1 in April 2021 calculated using only 2020 GADs (Single Year) and the pooled data over three years (Three Year graph).

The graph shows that the impact of pandemic on increasing the GAD for domestic customers is reflected on the single year profile coefficients, particularly over the working hours

The PEG recommended to the Supplier Volume Allocation Group (SVG) in February 2021 that the best methodology to use was the three year pooled data set because a single year set could be more volatile and may not be reflective of the situation in 2021. This recommendation to not deviate away from the usual methodology used in previous years was approved by the SVG.

Please note:

  • The GAD data covers year 2020 up to 6 September which is the last day in High Summer 2020. The remaining part of 2020 up to the March of 2021 will be provided by PrA in 2020/21 Autumn/Winter data samples.
  • Profile Coefficients are available through Market Domain Data on Elexon Portal.


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