Glossary

BSC Insights: Using Open Data to map the financial impacts of failed Suppliers

In this BSC Insight, Muhammad Raees Usman, Product Analyst in our Analysis & Insight Team, outlines how you can use newly Open Data from the BSC Modification P398 Open Data Request service to gain an insight into the energy market. He does this in view of the unprecedented market conditions experienced in the second half of 2021 and how these conditions led to a substantial number of Supplier default events. The article also provides an insight in to how Python can be used to ingest Open data files for analysis.

About our Open Data request service 

The introduction of the Elexon Open Data Request service was established following the approval of P398 ‘Increasing access to BSC Data’ in June 2021. P398 requires that all BSC data is considered open unless the BSC Panel decides otherwise.

The service has created a channel to allow industry to request the use of energy data and maximise its value. This service was also commissioned with the aim to help implement the recommendations of the Energy Data Taskforce.

The Energy Data Taskforce aims to establish a more modern, digitalised energy system by using the presumption that all data is open unless specific reasoning is given to prevent negative consumer or commercial impact.  

Elexon has now published over 380 data items to be readily available to industry under the Open Data License through the Open Data Request service. These data items can be used by industry to support improved decision making in the realm of market analysis, this could aid in initiatives such as the movement of the energy sector to a net zero carbon future.

Open Data maps financial impacts of failed Suppliers 

With the soaring wholesale energy prices observed in the second half of 2021, there was an unprecedented number of Suppliers that ceased trading. Customers of these Suppliers were protected by Ofgem and moved to a new Supplier using the Supplier of Last Resort (SoLR) process, as the ceased Suppliers had accumulated debt as they could no longer afford to supply their customers.

It can be particularly difficult for smaller Suppliers to withstand soaring wholesale prices as the maximum amount they can charge their customers is limited by the Ofgem energy price cap. Due to this unfortunate high number of defaults, there was an outstanding amount of bad debt that Elexon had to manage.

Elexon received an Open Data Request to release data relating to each Supplier that ceased to trade to enhance the visibility of their impact on market participants that continued to trade. The specific data requested consists of unpaid BSC trading charges that have been redistributed through the Default Funding Share (DFS).

The DFS consists of the share each BSC Party will pay to cover the cost of the Supplier default events. The graph below illustrates the DFS distribution up to the current month and also shows the cumulative number of Suppliers that have had a SoLR for context.

Graph 1: Unpaid BSC Trading Charges that have been redistributed through Default Funding Shares

The Failed BSC Parties that have ceased trading are identifiable in the graph using their BSC Party ID and there are also unpaid Trading Charges from BSC Parties that have not ceased trading. These Parties are grouped under BSC Party ID ‘ANON’ so that the publication of their unpaid Trading Charges does not negatively impact their ability to trade.

The graph shows that 26 BSC Parties defaulted since August 2021. The highest jump between two consecutive months was between August 2021 and September 2021 where 11 Suppliers defaulted in a single month. This in turn led to the highest total DFS amount of £22.1 M in a single month that has been observed by Elexon. The largest percentages of this DFS came from the Parties Avro Energy (£7.3M) and Green Energy Supply Limited (£4.4M).

Newly Open Data provides insight before cessation of trading 

Trading Charges that make up the DFS occur after a BSC Party has ceased trading. The Open Data Request process has also provided access for everyone to four hugely informative Settlement Reports, known under the umbrella of P114 Data:

  • SAA-I014 (subflow 2): everything that happened in the Settlement Systems on a particular day, broken down into half hour Settlement Periods
  • CDCA-I029: the energy consumption by each regional Grid Supply Point (GSP) Group in Great Britain
  • CDCA-I030: the volume of energy that was metered at each Distribution System Connection Point for each Settlement Run per day
  • CDCA-I042: the Metered Volumes of energy for each BM Unit for each aggregation run per day

The SAA-I014 (subflow 2) data flow was used to show the changes in Energy Imbalance Volumes for failed Suppliers before they have ceased trading. The Energy Imbalance Volume represents the difference in energy usage a BSC Party has contracted and their actual energy usage for each Settlement Period. BSC Parties are charged for each MWh of this Imbalance Volume at the Imbalance Price.

Therefore, the more Imbalance Volume a Party accumulates the more exposure the Party has to marginal Imbalance Price changes.

The graph below represents the trend of all ceased Suppliers in the second half of 2021 with their imbalance position and bilateral contract volumes for six months prior to their default date. The data plotted is largely below the x-axis, this is because Suppliers are generally in a negative imbalance position due to the short supply of energy in the market.

Graph 2: Sum of Energy Imbalance and Contract Volumes for all Defaulted Parties in the last 6 months of 2021

The graph indicates that struggling Parties, perhaps due to their lack of capital, tend to hedge less when buying energy in day-ahead and forward markets. This is observed in the data with Energy Imbalance Volumes being relatively stable until a significant decrease (13,100 MWh) of absolute contract volumes from approximately 25 days before default.

Therefore, this leads the Suppliers that have a deficit of energy to be more reliant on buying energy on the imbalance market at the Imbalance Price.

Buying energy on the imbalance market can be profitable for Suppliers in certain conditions. However, at this time, it was observed that with a lack of electricity on the grid, a short system is likely to lead to high Imbalance Prices, channelling to failing Suppliers having difficulty to satisfy their consumer’s daily demand.

In the graph below, the averages of Imbalance Prices for the last six months of 2019, 2020 and 2021 are plotted to illustrate that prices were significantly higher in 2021 than previous years.

Graph 3: Monthly average System Prices for the last 6 months of 2019, 2020 and 2021

There was an increase of 346% in the Imbalance Price between 2020 and 2021 in the month of September (the month we saw the highest number of defaults). Furthermore, spikes in Imbalance Prices reaching as much as £4038/MWh on 09/09/2021 made it very difficult for Suppliers to profit when buying from the Imbalance Market.

Identified trends 

This BSC Insight has identified trends in Settlement relating to failed Suppliers. These Suppliers tend to experience a dip in the absolute bilateral contract volumes in the weeks prior to their default date.

This results in an increase in the absolute volumes of the Party’s imbalance position as they are unable to keep up with demand. Therefore, to satisfy their consumers’ contracts, failing Suppliers are buying energy at high Imbalance Prices resulting in a breach of their Credit Cover arrangements. This leads them to default and cease trading.

Using Python to ingest Settlement Report 

BSC Party Account Period Data was used in the above analysis which can be derived from the open SAA-I014 data flow using technology such as Python programming. Using the Pandas data package in Python, the pipe delimited SAA-I014 text data files can be ingested for use.

The nested format of the data flow can prove to be tricky obstacle when attempting to retrieve the data of interest.

To identify the different data items within the file, users can map each field using the Interface Definition and Design (IDD) document. (This excel file represents one excerpt for the SAA-I014 data flow from the NETA IDD, which describes Elexon’s data flows).

Useful example

An example of a simple Jupyter notebook Python script is provided below via a Github link, to illustrate this process. This script takes the input of a BSC Party ID and outputs the Account Period Data for that Party on the Settlement Date and Run Type the file was generated for.

Please note that you will need Jupyter Notebook installed to run the script.

Future Open Data sets 

Elexon’s new wholesale market data service, the Insights Solution was launched in June 2022. It will eventually replace the ageing Balancing Mechanism Reporting Service platform. The Insights Solution provides industry with real time data visualisations and analytics built on state of the art cloud technology. In addition, best in class Application Programming Interfaces (APIs) are available to query data and allow for independent data analysis. 

Icebreaker One is helping to revolutionise the way data is shared across the energy sector. Elexon has collaborated with Icebreaker One by integrating ten data sets on their Open Energy platform. Elexon’s data, along with other data providers on the platform, will help industry to build a picture of the GB electricity market and how Net Zero goals can be reached.

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