UK Power Network maintains the 132kV voltage level network\nand below. An important part of the distribution network is the stepping down\nof voltage as it is moved towards the household; this is achieved using\ntransformers. Transformers have a maximum rating for the utilisation of these\nassets based upon protection, overcurrent, switch gear, etc. This dataset\ncontains the Grid Substation Transformers, also known as Bulk Supply\nPoints, that typically step-down voltage from 132kV to 33kV (occasionally down\nto 66 or more rarely 20-25). These transformers can be viewed on the single\nline diagrams in our Long-Term\nDevelopment Statements (LTDS) and the underlying data is then found in the LTDS tables.
This dataset provides half-hourly current and power\nflow data across these named transformers from 2021 through to the previous\nmonth across our license areas. The data are aligned with the same naming\nconvention as the LTDS for improved interoperability.
Care is taken to protect the private affairs of companies\nconnected to the 33kV network, resulting in the redaction of certain transformers.\nWhere redacted, we provide monthly\nstatistics to continue to add value where possible. Where monthly\nstatistics exist but half-hourly is absent, this data has been redacted.
To find which transformer you are looking for, use the \u2018tx_id\u2019\nthat can be cross referenced in the Grid Transformers Monthly Dataset, which describes by month what\ntransformers were triaged, if they could be made public, and what the monthly\nstatistics are of that site.
If you want to download all this data, it is perhaps more\nconvenient from our public sharepoint:\u00a0
This dataset is part of a larger endeavour to share more\noperational data on UK Power Networks assets. Please visit our Network Operational\nData Dashboard for more operational datasets.
The dataset is not derived, it is the measurements from our\nnetwork stored in our historian.
The measurement devices are taken from current transformers\nattached to the cable at the circuit breaker, and power is derived combining\nthis with the data from voltage transformers physically attached to the busbar.\nThe historian stores datasets based on a report-by-exception process, such that\na certain deviation from the present value must be reached before logging a\npoint measurement to the historian. We extract the data following a 30-min time\nweighted averaging method to get half-hourly values. Where there are no\nmeasurements logged in the period, the data provided is blank; due to the\nreport-by-exception process, it may be appropriate to forward fill this data\nfor shorter gaps.
We developed a data redactions process to protect the\nprivacy or companies according to the Utilities Act\n2000 section 105.1.b, which requires UK Power Networks to not disclose\ninformation relating to the affairs of a business. For this reason, where the\ndemand of a private customer is derivable from our data and that data is not\nalready public information (e.g., data provided via Elexon on the Balancing\nMechanism), we redact the half-hourly time series, and provide only the monthly\naverages. This redaction process considers the correlation of all the data, of\nonly corresponding periods where the customer is active, the first order\ndifference of all the data, and the first order difference of only\ncorresponding periods where the customer is active. Should any of these four\ntests have a high linear correlation, the data is deemed redacted. This process\nis not simply applied to only the circuit of the customer, but of the\nsurrounding circuits that would also reveal the signal of that customer.
The directionality of the data is not consistent within this\ndataset. Where directionality was ascertainable, we arrange the power data in\nthe direction of the LTDS \"from node\" to the LTDS \"to\nnode\". Measurements of current do not indicate directionality and are\ninstead positive regardless of direction. In some circumstances, the polarity\ncan be negative, and depends on the data commissioner's decision on what the\noperators in the control room might find most helpful in ensuring reliable and\nsecure network operation.
The data is provided \"as is\".
In the design and delivery process adopted by the DSO,\ncustomer feedback and guidance is considered at each phase of the project. One\nof the earliest steers was that raw data was preferable. This means that we do\nnot perform prior quality control screening to our raw network data. The result\nof this decision is that network rearrangements and other periods of non-intact\nrunning of the network are present throughout the dataset, which has the\npotential to misconstrue the true utilisation of the network, which is\ndetermined regulatorily by considering only by in-tact running arrangements.\nTherefore, taking the maximum or minimum of these transformers are not a\nreliable method of correctly ascertaining the true utilisation. This does have\nthe intended added benefit of giving a realistic view of how the network was\noperated. The critical feedback was that our customers have a desire to\nunderstand what would have been the impact to them under real operational\nconditions. As such, this dataset offers unique insight into that.
Creating this dataset involved a lot of human data\nimputation. At UK Power Networks, we have differing software to run the network\noperationally (ADMS) and to plan and study the network (PowerFactory). The\nmeasurement devices are intended to primarily inform the network operators of\nthe real time condition of the network, and importantly, the network drawings\nvisible in the LTDS are a planning approach, which differs to the operational.\nTo compile this dataset, we made the union between the two modes of operating\nmanually. A team of data scientists, data engineers, and power system engineers\nmanually identified the LTDS transformer from the single line diagram,\nidentified the line name from LTDS Table 2a/b, then identified the same transformer\nin ADMS to identify the measurement data tags. This was then manually inputted\nto a spreadsheet. Any influential customers to that circuit were noted using\nADMS and the single line diagrams. From there, a python code is used to perform\nthe triage and compilation of the datasets.
There is potential for human error during the manual data\nprocessing. These issues can include missing transformers, incorrectly labelled\ntransformers, incorrectly identified measurement data tags, incorrectly\ninterpreted directionality. Whilst care has been taken to minimise the risk of\nthese issues, they may persist in the provided dataset. Any uncertain behaviour\nobserved by using this data should be reported to allow us to correct as fast\nas possible.
Definitions of key terms related to this dataset can be\nfound in the Open\nData Portal Glossary.
Download dataset information: Download dataset information: Metadata (JSON)
We would be grateful if you find this dataset useful to\nsubmit a \u201creuse\u201d case study to tell us what you did and how you used it. This\nenables us to drive our direction and gain better understanding for how we\nimprove our data offering in the future. Click here for more information:\u00a0Open Data Portal Reuses \u2014 UK Power Networks
To view this data please register and login.
UK Power Network maintains the 132kV voltage level network\nand below. An important part of the distribution network is the stepping down\nof voltage as it is moved towards the household; this is achieved using\ntransformers. Transformers have a maximum rating for the utilisation of these\nassets based upon protection, overcurrent, switch gear, etc. This dataset\ncontains the Grid Substation Transformers, also known as Bulk Supply\nPoints, that typically step-down voltage from 132kV to 33kV (occasionally down\nto 66 or more rarely 20-25). These transformers can be viewed on the single\nline diagrams in our Long-Term\nDevelopment Statements (LTDS) and the underlying data is then found in the LTDS tables.
This dataset provides half-hourly current and power\nflow data across these named transformers from 2021 through to the previous\nmonth across our license areas. The data are aligned with the same naming\nconvention as the LTDS for improved interoperability.
Care is taken to protect the private affairs of companies\nconnected to the 33kV network, resulting in the redaction of certain transformers.\nWhere redacted, we provide monthly\nstatistics to continue to add value where possible. Where monthly\nstatistics exist but half-hourly is absent, this data has been redacted.
To find which transformer you are looking for, use the \u2018tx_id\u2019\nthat can be cross referenced in the Grid Transformers Monthly Dataset, which describes by month what\ntransformers were triaged, if they could be made public, and what the monthly\nstatistics are of that site.
If you want to download all this data, it is perhaps more\nconvenient from our public sharepoint:\u00a0
This dataset is part of a larger endeavour to share more\noperational data on UK Power Networks assets. Please visit our Network Operational\nData Dashboard for more operational datasets.
The dataset is not derived, it is the measurements from our\nnetwork stored in our historian.
The measurement devices are taken from current transformers\nattached to the cable at the circuit breaker, and power is derived combining\nthis with the data from voltage transformers physically attached to the busbar.\nThe historian stores datasets based on a report-by-exception process, such that\na certain deviation from the present value must be reached before logging a\npoint measurement to the historian. We extract the data following a 30-min time\nweighted averaging method to get half-hourly values. Where there are no\nmeasurements logged in the period, the data provided is blank; due to the\nreport-by-exception process, it may be appropriate to forward fill this data\nfor shorter gaps.
We developed a data redactions process to protect the\nprivacy or companies according to the Utilities Act\n2000 section 105.1.b, which requires UK Power Networks to not disclose\ninformation relating to the affairs of a business. For this reason, where the\ndemand of a private customer is derivable from our data and that data is not\nalready public information (e.g., data provided via Elexon on the Balancing\nMechanism), we redact the half-hourly time series, and provide only the monthly\naverages. This redaction process considers the correlation of all the data, of\nonly corresponding periods where the customer is active, the first order\ndifference of all the data, and the first order difference of only\ncorresponding periods where the customer is active. Should any of these four\ntests have a high linear correlation, the data is deemed redacted. This process\nis not simply applied to only the circuit of the customer, but of the\nsurrounding circuits that would also reveal the signal of that customer.
The directionality of the data is not consistent within this\ndataset. Where directionality was ascertainable, we arrange the power data in\nthe direction of the LTDS \"from node\" to the LTDS \"to\nnode\". Measurements of current do not indicate directionality and are\ninstead positive regardless of direction. In some circumstances, the polarity\ncan be negative, and depends on the data commissioner's decision on what the\noperators in the control room might find most helpful in ensuring reliable and\nsecure network operation.
The data is provided \"as is\".
In the design and delivery process adopted by the DSO,\ncustomer feedback and guidance is considered at each phase of the project. One\nof the earliest steers was that raw data was preferable. This means that we do\nnot perform prior quality control screening to our raw network data. The result\nof this decision is that network rearrangements and other periods of non-intact\nrunning of the network are present throughout the dataset, which has the\npotential to misconstrue the true utilisation of the network, which is\ndetermined regulatorily by considering only by in-tact running arrangements.\nTherefore, taking the maximum or minimum of these transformers are not a\nreliable method of correctly ascertaining the true utilisation. This does have\nthe intended added benefit of giving a realistic view of how the network was\noperated. The critical feedback was that our customers have a desire to\nunderstand what would have been the impact to them under real operational\nconditions. As such, this dataset offers unique insight into that.
Creating this dataset involved a lot of human data\nimputation. At UK Power Networks, we have differing software to run the network\noperationally (ADMS) and to plan and study the network (PowerFactory). The\nmeasurement devices are intended to primarily inform the network operators of\nthe real time condition of the network, and importantly, the network drawings\nvisible in the LTDS are a planning approach, which differs to the operational.\nTo compile this dataset, we made the union between the two modes of operating\nmanually. A team of data scientists, data engineers, and power system engineers\nmanually identified the LTDS transformer from the single line diagram,\nidentified the line name from LTDS Table 2a/b, then identified the same transformer\nin ADMS to identify the measurement data tags. This was then manually inputted\nto a spreadsheet. Any influential customers to that circuit were noted using\nADMS and the single line diagrams. From there, a python code is used to perform\nthe triage and compilation of the datasets.
There is potential for human error during the manual data\nprocessing. These issues can include missing transformers, incorrectly labelled\ntransformers, incorrectly identified measurement data tags, incorrectly\ninterpreted directionality. Whilst care has been taken to minimise the risk of\nthese issues, they may persist in the provided dataset. Any uncertain behaviour\nobserved by using this data should be reported to allow us to correct as fast\nas possible.
Definitions of key terms related to this dataset can be\nfound in the Open\nData Portal Glossary.
Download dataset information: Download dataset information: Metadata (JSON)
We would be grateful if you find this dataset useful to\nsubmit a \u201creuse\u201d case study to tell us what you did and how you used it. This\nenables us to drive our direction and gain better understanding for how we\nimprove our data offering in the future. Click here for more information:\u00a0Open Data Portal Reuses \u2014 UK Power Networks
To view this data please register and login.