Project Summary
The Data-2-Insights Project aims to improve the value and insight customers gain from our Open Data. It will build and test use cases to trigger a step change in the engagement with present and future Energy data.
D2I will also use technology to add value by improving data quality and consistency internally and externally and reduce the cost of providing digital solutions.
It will push the value of data to new levels helping realize our vision of a valuable, efficient, consistent and economically sustainable data ecosystem, delivering a curated service to the end user regardless of their energy data skills.
Innovation Justification
D2I is a straight to Alpha submission addressing Round 4 Challenge 1: greater use of machine learning and AI to optimise energy networks by supporting faster more efficient connections. D2I will provide a step change in engagement with energy data that can be supported through the advances in AI and other digital technologies.
Innovation
This one-of-a-kind approach will evaluate the benefits of applying leading-edge analytical techniques (including Natural Language Processing, Machine Learning, Explainable Artificial Intelligence and Generative Modelling) to carefully interrogate and interpret siloed disparate DNO data sources to present information needed by stakeholders (see appendix). These techniques and technologies will also be applied to the challenge of data that is missing, incomplete or sparse. The key marker of success will be the ease of use, and the low level of technical expertise required to acquire insights.
There are two main innovative aspects:
1. Remove technical barriers to customer insight journeys from DNO data
2. Employ state of the art models to understand how to collect, analyse and store data efficiently
The Alpha project will focus on key elements to inform the future vision of an efficient, consistent and economically sustainable data strategy, that delivers a curated service to the end user regardless of their data skills. Additionally, Alpha will identify use cases to demonstrate the value of the solution and reveal any data governance barriers that might prevent BaU deployment.
Beta will then build and test the technology layer required to return insights from queries (derived from stakeholder engagement), made on a large volume of siloed and sometimes incomplete data. D2I will revolutionize not only the access to data but also increase the value from advanced technology to improve data quality and consistency both internally and externally and reduce the cost of providing digital solutions while improving the customer experience.
Previous Projects
D2I will build on the data currently included in SSENs Open Data Portal and specifically the NeRDA NIA project. We will also consider learning from other projects looking to share network data including the SIF funded Powering Wales Renewably. D2I seeks to build on these by developing the ability of non-industry system stakeholders to understand and derive value from DNOs Open Data projects.
The Energy Systems Catapult report 'A strategy for modern digitalized energy system' and a recent report from the CreDO project, 'Data Sharing Principles, Framework and Architecture' will inform WP2.
SIF Funding
D2I will explore use of new unproven data management and analytical techniques to deliver robust, understandable and accessible insights for consumers from DNOs Open Data portals. SIF funding will serve to de-risk inclusion of leading-edge techniques to improve efficiency and optimize data collection and storage.
Readiness levels and counterfactual
Individual components that will feed into the solution are TRL7-9. The insights engine to bring the data sources together is low but will be at TRL5 by the end of Alpha. SSEN have experience integrating data platforms, therefore, the IRL will be 5 by the end of Alpha.
By focusing on commercial and integration readiness to ensure fair access to all stakeholders, D2I will demonstrate the direct and wider societal value of providing insights. This will inform decisions on the most appropriate commercial models for deployment to best serve the interests of all consumers.
Currently there is ambiguity around the 'correct' interpretation of data provided, taking time and skill to come to an informed decision. D2I will make it simpler for stakeholders to gain insights from the available data more quickly by using digital technologies to overcome the need for the deep industry skills.
D2I_appendix_Q4.pdf (opens in a new window) (/application/10157301/form/question/45953/forminput/129146/file/805483/download)
Impacts and Benefits
D2I aims to accelerate and reduce the cost of digitalisation across the energy sector, leading to an acceleration of decarbonisation and increase the deliverability of Net Zero and Clean Power 2030. D2I will remove barriers and provide stakeholders with enhanced access to the insights needed to support their Net Zero strategies and plans by applying leading edge analytical techniques. TheProject will deliver a model that could be adopted by other DNOs.
The pre-innovation baseline considers the cost of SSEN publishing real-time measurement data from all substations within SSEN's licenses. Stakeholders will either require specific expertise or contract specialist engineering consultants to deliver insights from the data.
D2I is designed to deliver both quantitative and qualitative benefits across the range of the listed SIF specific benefits areas. The benefits outlined below will deliver a net benefit to electricity customers both financially and environmentally.
Financial - future reductions in the cost of operating the network:
1. Cost of DNOs gathering and hosting data.
There is significant cost for DNOs to gather and publish data. This data cannot always be effectively used by stakeholders and in some instances is incorrect data. D2I will use data management and analytical techniques to reduce data errors and reduce hosting costs.
2. Reduction in speculative connection requests.
Providing stakeholders with insights is expected to lead to reduced speculative connection requests, therefore, reducing associated costs and improving workflow planning.
3. Enhanced capability to identify network capacity
DNO stakeholders and network planning teams will also benefit gaining the ability to identify capacity in the network for processing connection requests, leading to reduced engineering time required for each connection. Enhanced insights could also identify where in the network overloads are likely to occur preventing any overload related outages.
4.Lowering the cost of procuring flexibility services
D2I will enable innovators to introduce new flexibility services and products to the market creating more competition and reducing the cost of procuring flexibility services for DNOs.
Financial - cost savings per annum for users of network services:
5.Increased investor confidence
Trusted insights enable investors to reduce uncertainty and improve decision-making processes. By leveraging complex data into easy-to-understand and reliable insights investors will gain a deeper understanding of the network.
6. Reduced needs for specialist consultancies
By providing essential insights, the D2I project will reduce the number of days stakeholders require from consultancy services, bringing further cost savings for users of network services.
Environmental - carbon reduction -- indirect CO2 savings per annum
7. LCT uptake will be accelerated and reach Net Zero faster.
D2I will increase investor confidence and accelerate the connection of low carbon generation and storage so reducing the carbon intensity of electricity and supporting the transition to Clean Power 2030.
Revenues - improved access to revenues for users of network services:
8. New propositions from flexibility service providers
By making data and insights more accessible, D2I will enable Flexibility Service Providers to create new propositions enabling increased adoption of flexibility services. This will unlock network capacity could be used to generate revenues.
9.Improved access to national energy markets
Understanding where there is capacity on the network will enable renewable and storage developers to identify where they will have improved access to national energy markets, balancing mechanism (BM) and fast frequency response (FFS)markets.)
Revenues - creation of new revenue streams
10. Increased investor confidence
Open data contributes to innovation and economic growth, primarily through datasets that directly form part of value-added activities where data is the primary product or service. Businesses and innovators accessing open data can innovate, attract new customers, improve customer experiences and enhance their offering.
