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We are identifying parts of our licence areas where solutions on the distribution network can support transmission constraints now and into RIIO-ED2. This is particularly relevant in our Scottish licence area due to existing constraints, the unique topology and the different voltage control boundaries compared to England.
Through our Distribution Future Energy Scenarios we forecast future demand growth and the uptake of Low Carbon Technologies, renewables and other DERs. The forecasts ensure our approach is tailored to individual local communities by reflecting local environmental influences, the existing local network infrastructure and societal influences, such as age, employment and economic factors, among others.
Your future electricity grid
Supporting whole system solutions
SSEN is in the process of embedding a whole system approach across our entire business that embraces opportunities to collaborate with others to enhance consumer benefits and societal outcomes. These include:
- Increasing the efficiency around how we deliver services can lead to savings for customers.
- Enabling effective and efficient roll-out of LCTs and avoiding unnecessary customer and societal costs.
- Increased system resilience through a more holistic understanding of future impacts and a wider toolset of smart solutions, such as improving in-home energy efficiency to reduce demand.
- Developing a better understanding of what our customers and stakeholders need from us.
- Improving wider societal outcomes through improved support for our customers beyond net zero.
Decarbonisation of transport has huge potential to support decarbonisation of the energy system and vis-versa. Individually owned EVs or autonomous EV pools could have co-located hubs to reduce overall journeys, sharing electricity infrastructure and acting as electricity storage whilst plugged in to support the GB grid. Vehicle to Grid (V2G) solutions, where cars charge at times of low network constraint and low wholesale price, can then discharge to support the networks at peak time, provided they remain plugged in. This will bring down the overall GB peak demand, reducing the need for the most expensive and more carbon intensive power plants.
The whole system service to the grid could be managed by the EV supplier, an aggregator supplier or the local transport hub, aligned to some requirements set by the customer. The customer would not need to worry about when they charge, but simply plugin and let the innovative companies and systems will ensure the transport is available for their journey.
The Regional Energy System Optimisation Planning (RESOP) project will support knowledge sharing between network operators and stakeholders in the energy system, and will support the Scottish Government to deliver Scotland’s ambitious decarbonisation targets.
RESOP will deliver whole system growth scenario modelling to understand the impact of local strategies (including from local authorities, developers and other stakeholders) on the energy system, allowing for local communities to have a "greater say" in the development of the energy system and better informed decisions as they plot a course to net zero. Having this whole system view will help ensure communities can achieve their ambitions and economic growth can be delivered in a sustainable manner. Our aim is to identify where and when network investment will be needed to support these local objectives and to understand the impact of stakeholders plans on the energy networks and the role of low carbon technologies in managing the impact.
Through RESOP we have partnered with Dundee City Council to develop a whole system planning tool that will help support Dundee’s net zero target of 2045 and its green economic recovery. The tool will be able to factor in objectives and drivers for local authorities and businesses, such as protecting jobs and re-establishing economic growth, and incorporate them into local plans to assess the implications they may have on the local electricity network. RESOP will also be able to model the likely outcomes of any shifts in future scenarios to help inform local decision making on an ongoing basis.