Planning tomorrow's grid: FES, SSEP, RESP and the LTDS
By the end of this module you will be able to:
- Describe how FES, SSEP, RESPs, and CSNP fit together as a planning ecosystem
- Explain connections reform: from 770 GW queue to evidence-based assessment
- Evaluate the argument that Clean Power 2030 depends on data
- Name the DNO planning data products (DFES, Network Development Plans, capacity heatmaps) and where they publish
On 30 January 2026 the first transitional Regional Energy Strategic Plan was published, and the new planning machinery produced its first real output.
For years, regional energy planning in Great Britain was fragmented: each network, local authority and developer worked from its own assumptions. The Regional Energy Strategic Plans are meant to fix that by giving every region one evidence base. The first transitional RESP, published by NESO on 30 January 2026, was the first tangible product of that machinery: a shared regional picture that a council, a network and a connecting generator can all plan against.
It matters because the RESP is a data product before it is a document. It pulls FES scenarios down to the regional level, layers on each DNO's network capacity data, and reconciles them with local development plans. NESO has set out the schedule that follows: the RESP methodology in summer 2026, then eleven full RESPs by the end of 2028. This module is where the course's recurring argument lands, because none of that planning works without the data infrastructure the earlier modules described.
A national spatial plan is only useful if it reaches the ground. How does the country turn one Strategic Spatial Energy Plan into decisions a specific region can act on?
15.1 The planning ecosystem: FES and the SSEP
Four planning artefacts shape the GB grid: FES, SSEP, CSNP, RESP
Three of the four artefacts share an owner but not a cadence, running from annual to a five-year cycle, so evidence drawn from them is of different ages, and a regional plan phased from 2026 reads scenarios written on another clock.
FES, SSEP, CSNP, RESP: four parallel planning artefacts. Source: NESO FES 2024; NESO SSEP consultation; NESO CSNP draft; ENA RESP papers.
FES: Future Energy Scenarios
is now in its 15th edition. Published annually by NESO, FES models four pathways to 2050, each representing a different combination of policy ambition, technology development, and consumer behaviour. The four pathways are not predictions, they are scenarios that bracket the range of plausible futures for the GB energy system.
FES is the single most influential data publication in GB energy planning. Every investment decision by network companies references FES scenarios. Ofgem's price control assessments use FES as the basis for evaluating network company business plans. The connections queue is assessed against FES to determine which projects align with credible demand pathways. FES is not just a publication: it is the shared reference frame that makes coordinated planning possible.
The data inputs to FES are extensive. NESO draws on historical demand data, weather patterns, technology cost projections, government policy commitments, consumer behaviour surveys, and international energy market trends. The outputs include demand forecasts, generation mix projections, storage requirements, interconnector flows, hydrogen production, and transport electrification trajectories, all at national and regional granularity, projected annually to 2050.
SSEP: Strategic Spatial Energy Plan
The is the first-ever GB spatial plan for energy infrastructure. Expected in Autumn 2027, the SSEP will identify where different types of energy infrastructure should be located to achieve the national energy transition at lowest cost and with the least environmental impact. This is a fundamental shift from the current approach where individual projects choose their own locations and then apply for grid connections.
The SSEP answers questions that FES cannot. FES tells you how much offshore wind GB needs by 2035. The SSEP tells you where those wind farms should be located, considering grid capacity, seabed conditions, fishing impacts, environmental designations, and proximity to demand centres. FES tells you how many heat pumps will be installed. The SSEP helps determine where the distribution network reinforcement should be concentrated to accommodate them.
The data requirements for the SSEP are immense. It requires CIM-standardised network models from all 14 DNOs and the transmission operators. It needs demand forecasts at sub-regional granularity. It requires land use data, planning constraints, environmental designations, and transport infrastructure. It must integrate with Scotland's existing energy planning framework and Wales's devolved planning powers. The SSEP is arguably the most data-intensive planning exercise ever undertaken in GB energy.
15.2 From national plan to funded investment: RESPs, CSNP and ETYS
RESPs: Regional Energy Strategic Plans
Eleven translate the national SSEP into local action: one for Scotland, one for Wales, and nine for England. RESPs identify the specific infrastructure needs, workforce requirements, and stakeholder considerations for each region. They bridge the gap between NESO's national planning and the local authorities, communities, and businesses that must deliver the transition on the ground.
RESPs are data products. Each RESP draws on FES scenarios filtered to the regional level, local authority development plans, DNO network capacity data (published in CIM format under the LTDS programme), and regional economic data. The quality of each RESP depends directly on the quality and accessibility of the underlying data. This is where the transformation programmes described in Module 12 connect to real-world planning: without FMAR, RESPs cannot account for flexibility assets; without CIM-standardised network models, they cannot assess network capacity; without DSI, they cannot discover what data exists.
CSNP and ETYS
The determines which transmission investments should be funded. Under RIIO-3, the CSNP has a £28.1 billion budget for transmission network investment. The CSNP uses FES scenarios, SSEP spatial priorities, and network modelling to identify which reinforcements, new circuits, and substations are needed and when.
The (ETYS) provides the shorter-term complement: a ten-year forecast of transmission network needs. ETYS is published annually and provides the network planning data that informs both the CSNP and individual connection offers. Together, CSNP and ETYS create a planning pipeline from strategic vision (CSNP, 15-30 year horizon) through medium-term planning (ETYS, 10 years) to operational delivery.
15.3 DNO planning data: DFES, Network Development Plans and heatmaps
National planning is only half the picture. Each distribution network operator publishes its own regional planning data, and this is where most local decisions actually get made. The headline product is the , a regional counterpart to FES that each DNO produces (usually with the consultancy Regen) and publishes as open data. A then sets out the reinforcement each network needs to serve those scenarios, and quarterly capacity heatmaps show, area by area, where spare capacity to connect exists and where it does not. Together these let a developer or a local authority see the network before applying to it.
For that regional data to add up to a national picture, every network has to describe itself the same way. That is the job of the digitalisation programme. Ofgem is moving the LTDS from PDF documents to structured data published as profiles that are deltas from CGMES 3.0, the same common grid model taught in the previous module, so that a DNO network model and a transmission model speak one language. The rollout is staged from November 2025 to November 2026, and it is paired with a heatmap application programming interface that serves the capacity data in a machine-readable form. The wider ambition, coordinated through NESO's Data Sharing Infrastructure, is that a planner can discover and pull any network's capacity data without knowing in advance which of the 14 DNOs holds it.
What is the key difference between FES and the SSEP?
The scale of the problem is worth stating plainly. The connections queue held about 770 GW of applications against a GB peak demand of roughly 60 GW, so the queue ran to more than twelve times the demand the system will ever need. That is not a pipeline of real projects; it is a symptom of a first-come-first-served process that rewarded developers for filing speculative applications across many sites. Replacing it with evidence-based assessment depends entirely on high-quality data from FES, the CIM network models and FMAR.
15.4 Connections reform: from queue to evidence
Connections reform: from first-come queue to evidence-gated entry
The REFORM arrow separates a queue ordered by application date from one ordered by evidence, so a project now holds its place only while it keeps producing land rights, planning consent and capex at each annual review.
From first-come queue to evidence-gated entry. Source: NESO Connections Reform 2024; Ofgem CMP376; Clean Power 2030 connection commitments.
The most significant reform to GB electricity connections in decades was approved on 15 April 2025, when Ofgem accepted NESO's TMO4+ package (the code modifications CMP434 and CMP435, which NESO had submitted in December 2024). The connections queue had grown to approximately 770 GW of applications, more than twelve times GB's peak demand. Many of these applications were speculative: developers submitting applications for multiple sites knowing that most would not proceed, in order to secure a place in the queue under the first-come-first-served system. Gate 2 processing ran through 2025, with connection offers for 2030-aligned projects issued into early 2026.
The reform replaces first-come-first-served with evidence-based assessment. Instead of ordering applications by the date they were received, the new process assesses applications against criteria including project readiness, alignment with FES scenarios, contribution to Clean Power 2030, and deliverability within a realistic timeframe. The target is to reduce the queue from 770 GW to approximately 381.5 GW by removing speculative and non-viable applications.
The data requirements of evidence-based assessment
Evidence-based assessment is inherently data-intensive. To assess whether a project is aligned with FES scenarios, you need the FES data at sufficient granularity to evaluate the project's location and technology type. To assess deliverability, you need construction timeline data, supply chain information, and planning consent status. To assess network impact, you need CIM-standardised network models that show available capacity and constraint locations.
The reform exposes a dependency: evidence-based decisions require evidence-grade data. The evidence required for connections reform is precisely the data that the transformation programmes are designed to provide. FMAR provides flexibility asset visibility. CIM profiles provide network capacity data. FES provides demand and generation scenarios. The SSEP will provide spatial priorities. Connections reform is not just a process change, it is a data change.
Carbon Intensity API and data quality
The Carbon Intensity API demonstrates what is possible when energy data is standardised, accessible, and well-governed. The API provides 30-minute granularity carbon intensity data across 14 GB regions, with 96-hour forward forecasts. It is openly accessible, well-documented, and has been adopted by hundreds of organisations for applications ranging from data centre scheduling to EV charging optimisation.
The Carbon Intensity API works because it sits on top of clean, consistent operational data from NESO's control room systems. The generation mix data is accurate. The regional allocation methodology is transparent. The forecast models are validated against actual outcomes. This is the data quality standard that the rest of the energy data ecosystem needs to achieve.
The data quality pipeline matters as much as the data itself. Raw meter readings contain errors, gaps, and anomalies. Network models contain approximations and out-of-date information. Consumer data contains duplicates, formatting inconsistencies, and incomplete records. Every data-driven application, from connections assessment to demand forecasting to digital twins, depends on a quality pipeline that validates, cleanses, and enriches raw data before it becomes usable. The transformation programmes must deliver not just data access but data quality.
Common misconception
“Connections reform is just an administrative change to the queue management process.”
Connections reform is a fundamental shift from chronological ordering to evidence-based assessment. It requires data infrastructure that largely does not yet exist: FES at sub-regional granularity, CIM network models with capacity data, FMAR for flexibility visibility, and SSEP for spatial priorities. The reform cannot succeed without the data transformation programmes delivering on their timelines.
15.5 Clean Power 2030 depends on data
Clean Power 2030 stands on data: four dependency layers
The policy sits at the top and the network model with the connections evidence at the bottom, and the arrow runs upward, so the 2030 commitments can be evidenced only as far as the publications beneath them allow.
Clean Power 2030 depends on real-time data, network model, and connections evidence. Source: DESNZ Clean Power 2030 Plan; NESO Beyond 2030 papers.
DESNZ describes the Strategic Spatial Energy Plan as the most significant spatial planning exercise ever undertaken in the UK energy sector, drawing on data from across the electricity, gas, heat and transport systems. Its data requirements are large in scale: CIM-standardised network models from all 14 DNOs, demand forecasts at sub-regional granularity, and land use, environmental and planning data across England, Scotland and Wales. Every data infrastructure gap translates directly into SSEP uncertainty.
The argument that Clean Power 2030 depends on data is not rhetorical. It is structural. Every element of the decarbonisation pathway requires data infrastructure that is either incomplete or under construction.
Connecting 50 GW of offshore wind requires connections reform, which requires evidence-based assessment, which requires CIM network models, FES scenarios, and SSEP spatial priorities. Integrating millions of heat pumps requires distribution network reinforcement, which requires DNO visibility of low-voltage network loading, which requires smart meter data flowing through MHHS. Unlocking demand-side flexibility requires FMAR for asset visibility, MHHS for accurate settlement, and the SDR for consumer data access that enables third-party flexibility services.
Each link in these chains is a data dependency. Break any link and the downstream capability is degraded. The planning ecosystem of FES, SSEP, RESPs, CSNP and ETYS is only as good as the data it consumes. The market infrastructure of connections reform, settlement and flexibility dispatch is only as effective as the data that informs it. The consumer services of tariff optimisation, EV smart charging and home energy management are only as useful as the data they can access.
This is not a future problem. It is a present problem. The decisions being made today about which wind farms to connect, which networks to reinforce, and which flexibility services to procure are being made with incomplete data. Good data governance is not a bureaucratic formality. It is the prerequisite for decisions of this scale and consequence. The transformation programmes will improve this, but the critical planning decisions for Clean Power 2030 cannot wait until 2028 or 2030 for perfect data. They must be made with the best available data now, and improved iteratively as the data infrastructure matures.
The honest conclusion is that Clean Power 2030 will be achieved, or not, in part because of data infrastructure. Not solely because of it: policy, investment, supply chains, planning consent, and public acceptance all matter enormously. But data is the connective tissue that links all of these elements. Without it, planning is guesswork, markets are inefficient, and consumers are disconnected from the transition that is reshaping their energy system.
What replaced the first-come-first-served connections process under the TMO4+ package Ofgem approved on 15 April 2025?
Core distinctions
- The planning ecosystem forms a hierarchy: FES (how much, 4 pathways to 2050) feeds SSEP (where, Autumn 2027) feeds 11 RESPs (local action) feeds CSNP (GBP 28.1bn transmission investment). ETYS provides the 10-year bridge.
- Connections reform (TMO4+, approved by Ofgem on 15 April 2025) replaces first-come-first-served with evidence-based assessment, reducing the queue from 770 GW to about 381.5 GW. This reform depends on data from FES, CIM models, FMAR, and SSEP.
- The Carbon Intensity API (30-min, 14 regions, 96-hour forecast) demonstrates the standard that the rest of the energy data ecosystem needs to achieve: clean data, standardised access, transparent methodology.
- Every element of Clean Power 2030 has a data dependency. Offshore wind needs connections data. Heat pumps need distribution network data. Flexibility needs FMAR and MHHS data. Break any data link and the downstream capability is degraded.
- Data is the connective tissue of decarbonisation: it links planning, markets, and consumer services into a coherent system. Without it, the energy transition operates on guesswork.
Standards and sources cited in this module
NESO. Future Energy Scenarios 2025 (15th edition)
Scenario framework, demand projections, and methodology
The foundational planning publication for GB energy. Source for the four-pathway scenario framework, regional demand projections, and the data inputs that inform every downstream planning decision.
Ofgem. Summary decision: TMO4+ package (CMP434 and CMP435)
Approval of the connections reform code modifications
Primary source for the date and content of the connections reform approval on 15 April 2025, the package NESO submitted in December 2024. Referenced in Section 15.4.
NESO. Connections Reform: Outcome of Consultation, December 2025
Evidence-based assessment criteria and queue management
Source for current connections reform status, queue-management design, and ready-to-build pipeline reporting.
DESNZ. Strategic Spatial Energy Plan: commission to NESO, 2024
SSEP scope, methodology and data requirements
Source for the SSEP as the first-ever GB spatial energy plan, its relationship to FES and RESPs, and the data requirements that make it the most data-intensive planning exercise in GB energy history.
Module 26 of 31 in Energy System Data