SPEN: Realising the benefits of modelling beyond regulatory framework

 SP Energy Networks is a regulated business focused on delivering industry changing projects,with Transmission investments of £2.6Bn (2013-2021) and Distribution investments of £4.4Bn (2015 to 2023). They provide power to:

• 1.5 million customers in Merseyside, Cheshire, North Wales and North Shropshire; and

• 2 million customers in Central and Southern Scotland

The Story

To improve their asset management processes and increase the robustness of their investment planning activities following the RIIO-ED1 business planning process, SP Energy Networks engaged EA Technology in 2014 to implement an integrated software system across their Distribution and Transmission network operations.This solution was known as CBRM, short for Condition Based Risk Management.

Since then, we have developed a strong relationship with SP Energy Networks and have established ourselves as a trusted provider. During this time, we have:

• Developed bespoke CBRM models for their distribution and transmission assets

• Provided on-going support and training whilst the CBRM process has become embedded throughout SP Energy Networks asset management activities

• Migrated the bespoke CBRM models to regulatory reporting Common Network Asset Indices Methodology (CNAIM) and Network Output Measures (NOMs) models

•Developed bespoke reporting to assist with the regulatory reporting requirements

Solutions

The first phase of the journey with SP Energy Networks involved the creation of bespoke models for all major asset types, including transformers, switchgear, overhead lines and cables at all voltage levels from LV to 400kV. Following the deployment of the models, we provided a series of calibration workshops to ensure the results from the models reflected SP Energy Networks experience.
These workshops collated the views and experiences from asset managers and engineers responsible for the maintenance of the assets, as well as introducing and training of the model calibration process. This provided SP Energy Networks with the skills necessary to undertake any updates to their calibration in future years as part of their ongoing cycle of continual improvement. SP Energy Networks were also equipped with a deep understanding of the CBRM process, enabling them to take an active role in the development of the CNAIM, the methodology created by Great Britain’s distribution network operators (DNOs) for regulatory reporting.Following the introduction of CNAIM, the bespoke models for the distribution assets were migrated to the new regulatory reporting models. Bespoke data mapping was provided to utilise the data already used for the bespoke models and match it to the strict input types required by the regulatory reporting models. In addition, we provided a range of customised reports to assist with the regulatory reporting requirements.

Specialised models were developed to enable the impact of interventions to be modelled using the CNAIM framework, thus enabling SP Energy Networks to quantify the future
risk after an intervention program, and to evaluate the impact of any intervention program through the quantification of the delta risk.

The CNAIM came into force after the start of the RIIOED1 regulatory period (2015-2023). Therefore, the DNOs were required to restate their investment plans for the on-going regulatory period (RIIO-ED1) using the newly approved methodology. This required the restatement of the health and criticality profiles at the start of RIIO-ED1 (i.e. in 2015), the expected profile at the end of 2023 with and without investment, and also to report progress made at the end of year 1. Due to the significant amount of work required and the short time constraints imposed by the regulator, EA Technology provided on-site support to SP Energy Networks for this activity. This enabled us to help ensure that the client data previously used in CBRM had been mapped across correctly into the new models, to assist with the importing of investment plans into the models. The results of this were reported to the regulator to evaluate whether the investment plans assessed using the new methodology were ‘equally as challenging’ as those submitted prior to the introduction of CNAIM, i.e. did the investment plans still represent value for money for customers. Where-as the DNOs were able to adopt a common approach to reporting health and criticality, historical reasons meant that this approach was not adopted by the three GB Transmission Network Operators (TNOs). Instead, each TNO decided to retain their existing approach to determining asset health and probability of failure, whilst adopting a common approach to reporting consequences of failure and risk. Following the approval of this approach, referred to as NOMs, SP Energy Networks’ bespoke CBRM models were modified to align with the requirements of NOMs. During this work on NOMs, SP Energy Networks wished to extend the use of their bespoke CBRM models to include additional assets not currently covered by the reporting requirements, namely Disconnectors, Earth Switches and Instrument Transformers. By this time, EA Technology had released our new suite of Asset Investment Management (AIM) standard models.

With the CBRM process firmly embedded within their asset management processes, SP Energy Networks had the confidence to implement models for these new asset types using the new AIM framework. A series of design workshops were held in November 2018 to design the models to meet their requirements. These models were designed to reflect both their existing maintenance practices and procedures as well as accommodating best practice to facilitate SP Energy Networks’ on-going commitment to continual improvement. Alongside these new models, specialised ‘sandpit’ models were developed to allow ‘what if scenarios’ to be explored, by allowing engineers to explore in detail the potential impact of asset interventions.

Outcome

SP Energy Networks, in a few short years, have implemented an effective and responsive risk management strategy and framework that reduces exposure and harm and maximises asset performance. This framework forms part of SPEN’s enterprise risk reporting framework, which embeds risk management into the heart of the organisation’s governance process. The CNAIM and NOMs models sit within this framework, providing a standardised method of quantifying network risks associated with asset replacement and aligning them directly to the RIIO-ED1 outputs and incentives mechanism.