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Hydrogen Turbines Follow On - Scenario 10 Results Pack - Cost-optimal pathways to decarbonising the GB power sector - Final Report


Citation Baringa Partners LLP Hydrogen Turbines Follow On - Scenario 10 Results Pack - Cost-optimal pathways to decarbonising the GB power sector - Final Report, ETI, 2017. https://doi.org/10.5286/UKERC.EDC.000136.
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Author(s) Baringa Partners LLP
Project partner(s) Baringa Partners LLP
Publisher ETI
DOI https://doi.org/10.5286/UKERC.EDC.000136
Download AdHoc_CCS_CC1011_4.pdf document type
Abstract Optimal annual decarbonisation pathways to 2050 considering capacity and operational dispatch requirements, and current policy momentum effects
  • ETI commissioned Baringa to undertake detailed analysis of what the cost optimal power sector capacity mix could look like around the 2030 point on the pathway to 2050, which allows for feasible operation (in line with GB’s reliability standard for a loss of load expectation of 3 hours per year) and which is consistent with a trajectory that enables the UK to meet its longer term, economy-wide emissions target.
  • The analysis was undertaken in PLEXOS using the LT Plan (Long-Term) functionality that is available. A model was developed that minimises the total costs (capital, fixed operating and variable operating costs) of generation while ensuring the security of supply and meeting the carbon targets. For existing capacity wehave used our detailed in-house generation database that includes all power plants that participate in the wholesale markets along with their operational characteristics. The plant retirement decisions are an exogenous input to the model.
  • The costs of new entry capacity were mainly advised from the ESME database while the operating characteristics were a combination of ETI data supplemented by additional Baringa information where relevant (e.g. ramp rates or start costs for more detailed operational analysis which are not present in the ESME database). Fossil fuel prices were based on near term forward prices and International Energy Agency’s (IEA) long-term projections as the most recent available set of assumptions. A carbon intensity target was set at 90gCO2/kWh for 2030 and to net zero carbon emissionsfor 2050 (linear interpolation in between)
  • We simulated the GB power market for the horizon of 2022 to 2050 using the inputs described above. The simulation was run on annual basis with a reduced chronology (6 sample days per year with hourly dispatch and representation of interconnected market prices from Baringa’s pan-European power model). In the period 2022-2030, all coal and some older gas plants are decommissioned. The carbon intensity target remains high during that period and many technologies such as CCS and Nuclear remain expensive. As a result most of new capacity deployment comes from CCGT.
  • Most of the peaking capacity requirements for that period are met by OCGTs. In the period 2030-2050, carbon intensity target drops significantly and therefore there is need for more low carbon capacity. In this period, Nuclear is the dominant baseload capacity build and required new peaking additions are met by compressedair electricity storage and pumped heat electricity storage, on top of the existing pumped hydro capacity (from a set of battery and flow battery options).
Detailed analysis of cost-optimal annual decarbonisation pathways to 2050 considering capacity and operational dispatch requirements, and current policy momentum effects
  • Using the optimised pathway capacity mix, we also simulated the 2030 spot year in a detailed way (full hourly dispatch), generating projections of dispatch and prices for that year. Whilst the pathway analysis applied direct CO2 intensity constraint as part of the optimisation, using outputs from this analysis it is possible to infer what level the carbon price would have to reach to meet the 2030 intensity target. This requires ~58GBP per ton of CO2 to achieve the equivalent 90gCO2/kWh target given the Base Case capacity mix in 2030. In terms of the broader system operation in 2030 most of the flexibility is provided by CCGTs while OCGT only generates at periods of very high net load (demand net of wind and solar generation). Gas CCS and Nuclear are used for baseload generation.
  • In addition, we ran several sensitivities and compared these to the base case (alongside a range of other National Grid, CCC, ETI and Baringa scenarios):?
    • In Low Demand, significantly less baseload capacity is built over the entire horizon especially nuclear and CCS
    • In Low Fuel Prices, Gas CCS is favoured as the main baseload unit at the expense of nuclear
    • In Low Interconnection, there is need for more capacity - especially baseload because GB is expected to be a net importer in the medium term
    • In High Renewables, the need for baseload capacity decreases but additional OCGTs and storageunits are required to provide peak / flexible capability
    • In Flexible EVs, the flexibility of the electric vehicles reduces the requirement for dedicated storage units
    • In Constrained CCS, the restrictions of CCS in the 20s/early 30s, causes a permanent change to the system favouring renewables and storage
    • In Constrained Nuclear, the restrictions of nuclear in the 20s favour the deployment of CCS technologies and renewables
Associated Project(s) ETI-CC1011: Salt Cavern Appraisal for Hydrogen Power Generation Systems
Associated Dataset(s) No associated datasets
Associated Publication(s)

Hydrogen Turbines Follow On - A Review of Selected New CO2 Capture Technologies

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Hydrogen Turbines Follow On - CCS and H2 Dispatch modelling - Scenarios 1 & 2 Results Pack

Hydrogen Turbines Follow On - CCS and H2 Dispatch modelling - Scenarios 3 & 4 Results Spreadsheet

Hydrogen Turbines Follow On - CCS and H2 GT Dispatch modelling scenario 1 and 2 results spreadsheet

Hydrogen Turbines Follow On - Power Sector CCS and H2 Turbine Asset Modelling - Central Decarb market modelling results

Hydrogen Turbines Follow On - Review of Gas Turbines and their Ability to use Hydrogen-Containing Fuel Gas

Hydrogen Turbines Follow On - Salt Cavern Appraisal for Hydrogen and Gas Storage - Appendices

Hydrogen Turbines Follow On - Salt Cavern Appraisal for Hydrogen and Gas Storage - Final Report

Hydrogen Turbines Follow On - Scenario 1,2 and 3 Results Spreadsheet: Role of Gas/H2 in the GB power sector - initial analysis

Hydrogen Turbines Follow On - Scenario 10 Results Spreadsheet - GB Capacity Mix Optimisation - Results

Hydrogen Turbines Follow On - Scenario 5 Results Pack - Power sector CCS and H2 Turbine Asset Modelling

Hydrogen Turbines Follow On - Scenario 5 Results Spreadsheet

Hydrogen Turbines Follow On - Scenarios 1,2 and 3 Results Pack Report - The role of Gas/H2 in the GB power sector - initial analysis