1. What are the contributions in "Designing low-carbon power systems for great britain in 2050 that are robust to the spatiotemporal and inter-annual variability of weather" ?
To provide detailed insights into the transition to a power system with high shares of VREs, the authors need to combine long-term planning with a representation of the spatial and temporal variability of VREs, including the inter-annual characteristics of VRE production and their integration options.. In this study the authors combine the following key aspects which are important in understanding the design of future energy systems with high shares of VREs and ultimately achieve long term decarbonisation targets: a representation of the inter-annual variability of weather and its effect on system planning and VRE supply ; the spatial and temporal detail necessary to account for differences in VRE output and timing of production, demand and infrastructure ; modelling of the trade-offs and interaction of different VREs integration options ; and a whole energy systems view to consider the electrification of other sectors and an internally consistent assessment of the mitigation burden placed on the electricity sector.. The authors demonstrate this by using a modelling approach that soft-links a long-term ESM ( UKTM ) to a high spatial and temporal resolution PSM ( highRES ) ( see Methods ).. The authors apply their modelling approach to Great Britain ( GB ), a country with limited interconnection ( 7 % of peak demand ) and where national energy security is a high public and political priority41.. Their modelling approach soft-links a long-term ESM ( UKTM ) to a high spatial and temporal resolution PSM ( highRES ).. In their methodology the authors aim at a balanced approach between spatiotemporal resolution, temporal coverage ( i. e. how many weather years they consider ) and technical detail ( i. e. focusing on system adequacy and using a simplified grid representation ).. However, like the system operator National Grid in its modelling47 the authors follow the recommendation48 by the UK government ( Office of Gas and Electricity Markets, Ofgem ; Department for Business, Energy and Industrial Strategy, BEIS ) and implement load shedding at a cost set to the Value of Lost Load of 6000£/MWh.. The authors use the PSM to study the sensitivity of system planning and operation due to inter-annual weather variability by using ten different weather years to drive VRE production.. The authors also compare these results to when their PSM considers a 10-year continuous time series.. 4 Solar PV Capacity ( GW ) 10 44 50 Onshore Wind Capacity ( GW ) 9 32 27 Offshore Wind Capacity ( GW ) 5 39 68 Biomass Capacity ( GW ) 5 7 0. 4 Interconnection Capacity ( GW ) 5 6 3. 6 Storage Capacity ( GW ) 3 ( pump storage ) decided by highRES decided by highRES Hydropower Capacity ( GW ) 2 2 1. 6 Other Capacity ( GW ) 1 0. 5 0. 5 Electricity demand ( GWh ) 358,363 516,882 416,757 CO2 grid intensity ( gCO2/kWh ) 334 4. 4 4. 9 a ref. 69 b ref. 70 c ref. 71 d ref. 72 e ref. 73 50VRE and 80VRE scenarios are based on UKTM unless otherwise indicated For each scenario the authors study two different cases in highRES: optimising all three flexibility options ( allflex ) ; and optimising flexible generation and storage only and they fix the transmission network to its 2015 capacities ( flex+store ).. Further, by averaging multiple years or using a single weather year most of these studies neglect the inter-annual variability of weather.. If additional flexibility ( e. g. on the demand side ) is unavailable, the authors find that systems planned on the basis of one weather year can lead to operational inadequacy and failure to meet long term carbon targets placed on the sector as part of the decarbonisation of the whole energy system.. The authors choose not to include demand side measures as the large scale 3 implementation in the domestic and non-domestic sector and further uptake for industry are uncertain12,43,44 due to the inherent challenges around behaviour change facing non cost-barriers33,45 and as a result studies and data on costs are limited46, even more so from a spatial distribution perspective ( see Supplementary Note 9 ).. The authors differ between these two scenarios as, on the one hand, transmission line extension can take decades from conception to completion, with the planning system being a 4 fundamental barrier49, yet on the other hand it can unlock the benefits of greater spatial diversification.. Here, the authors can infer that a spatially diversified VRE portfolio leads to a lower utilisation of flexible generation.
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2. What are the key characteristics of the UKTM?
A large variety of future supply and demand technologies are represented by techno-economic parameters such as the capacity factor, energy efficiency, lifetime, capital costs, operation & maintenance costs.
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3. What is the main purpose of the UKTM?
In addition to its academic use, UKTM is the central long-term energy system pathway model used for policy analysis at the Department of Energy and Climate Change (DECC) and the Committee on Climate Change (CCC) 64,65 UKTM is a linear, bottomup, technology-rich cost optimising model instantiated within the TIMES framework60–63.
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4. What is the main strength of UKTM?
UKTM represents the entire UK energy system from imports and domestic production of fuel resources, through fuel processing and supply, explicit representation of infrastructure, conversion to secondary energy carriers (including electricity, heat and hydrogen), end-use technologies and energy service demands.
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