Embodied carbon dioxide of network assets in a decarbonised electricity grid

Calculating carbon dioxide ( {CO} 2 ) emissions associated with electricity is a key component in the field of Life Cycle Assessment (LCA), but is often cited as challenging due to the complex nature of electricity systems despite its importance to the outcome. While calculating the operational {CO} 2 emissions associated with electricity generation is an active research field, the embodied {CO} 2 emissions, typically referred to as embodied carbon, of network assets has far less representation in the literature. This paper focuses on the {CO} 2 emissions aspect of {LCA} to calculate the embodied {CO} 2 of network assets in relation to the operational grid {CO} 2 over time. Several functional units are defined: {CO} 2 per operational year, {CO} 2 per asset cost, {CO} 2 per functional unit of electricity (kW h) and the relationship between embodied emissions and operational emissions in an electricity system over time. Hybrid functional units are then applied in order to better attribute the embodied carbon to the network functions. The hybrid functional units involve network asset lifetime and the issue of temporal horizons. Several suitable horizons are suggested and the comparison of results highlight the importance of the timeframe on results. The relationship between temporal horizons and environmental discounting is discussed and recommendations are made on the appropriate level of discounting depending on the temporal horizon and the purpose of the LCA. The paper uses data from the Great Britain electricity system where planned investment in network assets is £12bn at distribution level (Dx) and £16.4bn at transmission level (Tx) over the next eight years. By using {GB} network data for embodied carbon, demand and asset data, as well as data from the decarbonisation of electricity generation, indicative results are provided into the way in which embodied carbon impacts could change over time, showing that by 2035, the embodied carbon of the transmission network could contribute almost 25 of total emissions associated with electricity. On a regional basis, {DNO} level network assets could reach anywhere between 40 and 130. This network data is also used to show that new network investment could account for up to 6.5 of {DNO} level network embodied carbon when front loaded during the RIIO-ED1 period

Identifying and characterising large ramps in power output of offshore wind farms

Recently there has been a significant change in the distribution of wind farms in Great Britain with the construction of clusters of large offshore wind farms. These clusters can produce large ramping events (i.e. changes in power output) on temporal scales which are critical for managing the power system (30 minute, 60 minute and 4 hours). This study analyses generation data from the Thames Estuary cluster in conjunction with meteorological observations to determine the magnitude and frequency of ramping events and the meteorological mechanism. Over a 4 hour time window, the extreme ramping events of the Thames Estuary cluster were caused by the passage of a cyclone and associated weather fronts. On shorter time scales, the largest ramping events over 30 minute and 60 minute time windows are not associated with the passage of fronts. They are caused by three main meteorological mechanisms; (1) very high wind speeds associated with a cyclone causing turbine cut-out (2) gusts associated with thunderstorms and (3) organised band of convection following a front. Despite clustering offshore capacity, the addition of offshore wind farms has increased the mean separation between capacity and therefore reduced the variability in nationally aggregated generation on high frequency time scales

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified

The impact of future offshore wind farms on wind power generation in Great Britain

In the coming years the geographical distribution of wind farms in Great Britain is expected to change significantly. Following the development of the “round 3” wind zones (circa 2025), most of the installed capacity will be located in large offshore wind farms. However, the impact of this change in wind-farm distribution on the characteristics of national wind generation is largely unknown. This study uses a 34-year reanalysis dataset (Modern-Era Retrospective Analysis for Research and Applications (MERRA) from National Aeronautics and Space Administration, Global Modeling and Assimilation Office (NASA-GMAO)) to produce a synthetic hourly time series of GB-aggregated wind generation based on: (1) the “current” wind farm distribution; and (2) a “future” wind farm distribution scenario. The derived data are used to estimate a climatology of extreme wind power events in Great Britain for each wind farm distribution. The impact of the changing wind farm distribution on the wind-power statistics is significant. The annual mean capacity factor increased from 32.7% for the current wind farm distribution to 39.7% for the future distribution. In addition, there are fewer periods of prolonged low generation and more periods of prolonged high generation. Finally, the frequency and magnitude of ramping in the nationally aggregated capacity factor remains largely unchanged. However, due to the increased capacity of the future distribution, in terms of power output, the magnitude of the ramping increases by a factor of 5

The importance of forecasting regional wind power ramping: a case study for the UK

In recent years there has been a significant change in the distribution of wind farms in Great Britain, with a trend towards very large offshore farms clustered together in zones. However, there are concerns these clusters could produce large ramping events on time scales of less than 6 hours as local meteorological phenomena simultaneously impact the production of several farms. This paper presents generation data from the wind farms in the Thames Estuary (the largest cluster in the world) for 2014 and quantifies the high frequency power ramps. Based on a case study of a ramping event which occurred on 3rd November 2014, we show that due to the large capacity of the cluster, a localised ramp can have a significant impact on the cost of balancing the power system on a national level if it is not captured by the forecast of the system operator. The planned construction of larger offshore wind zones will exacerbate this problem. Consequently, there is a need for accurate regional wind power forecasts to minimise the costs of managing the system. This study shows that state-of-the-art high resolution forecast models have capacity to provide valuable information to mitigate this impact

EV smart charging: how tariff selection influences grid stress and carbon reduction

With the rapid increase in ownership of Electric Vehicles (EVs), widespread concern has been raised regarding the potential for EV charging demand to overload electricity grids. Smart control of charging is advocated as a solution, gaining attention from business and support from policymakers. However, the ultimate grid benefits (or disbenefits) of smart charging will follow from a combination of user behaviour and pricing arrangements / tariffs. Local clustering of vehicle uptake can lead to unintended consequences as national incentives fail to align with local pressures. In this paper, we describe a simulation of the dynamic electricity demand pattern arising from a fleet of grid connected EVs. The model developed for this study combines stochastic sampling of data from a UK-based smart charging trial (Western Power Distribution’s Electric Nation project) with a set of plausible tariffs, including a strategy which specifically seeks to minimize grid carbon emissions. This provides insights into the potential impacts of EV charging by encompassing a wider range of tariffs than previously assessed, while also separating the control actions of optimising cost and managing capacity. We examine the carbon implications of tariff choice and introduce a range of grid overload metrics that reveal nuances in the tariff implications and evolution of impacts as EV penetration increases. The results show that smart charging is not necessarily a better solution for the grid compared to on-demand charging. Stepwise tariffs, currently favoured by UK energy suppliers, present a particular risk. Such tariffs can tend to increase load synchronization by shifting load towards periods where more cars are connected and awaiting charge. This can lead to an increased peak load even at moderate EV uptake levels. Dynamic tariffs proved preferable but still increase peak demand at higher vehicle uptakes. All smart tariffs offer a strong carbon benefit, but, again, current stepwise tariffs are failing to realise the full potential that could be realized by targeting low carbon time periods. Separate local capacity management was able to eliminate overload at the secondary substation, even with very high EV uptake, with only rare, very small levels of unserved demand

Interannual weather variability and the challenges for Great Britain’s electricity market design

Global growth in variable renewable generation has brought significant attention to the challenge of balancing electricity supply and demand. However, inter-annual variability of energy resources has only recently begun to feature in energy system assessments and receives limited recognition in policy discussion, let alone policy design. Meteorological reanalysis datasets that blend modern modelling techniques with historic weather records are seeing increased application in energy system studies. This practice offers insights for market and policy design implications as governments seek to manage the changing energy landscape, as seen with the UK’s introduction of the Electricity Market Reform policy package. Here we apply a concise, Load Duration Curve based approach to consider the market and policy implications of increasing variability in the Great Britain (GB) energy system. Our findings emphasise the growing inter-annual variability in operating opportunity for residual mid-merit and even baseload generation, alongside implications for capacity assurance approaches. The growth in wind generation is seen to bring an accompanying opportunity for increased solar generation, with its lower inter-annual variability and largely uncorrelated annual characteristic. The results underscore the need for an increased recognition of inter-annual variability when addressing market design and incentive mechanisms

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network

Sunny windy Sundays

Rapid expansion of wind and solar capacity in Great Britain presents challenges for managing electricity systems. One concern is the reduction in system inertia during periods where renewables provide a high proportion of demand which has led to some networks imposing system nonsynchronous penetration limits. However, given the lack of operational data, the relationship between renewable generation and demand for the full range of meteorological conditions experienced in Great Britain is poorly understood. This study uses reanalysis datasets to determine the proportion of demand from renewable generation on an hourly resolution for a 36-year period. The days with highest penetration of renewables tend to be sunny, windy weekend days between May and September, when there is a significant contribution of both wind and solar generation and demand is suppressed due to human behaviour. Based on the current distribution of wind and solar capacity, there is very little curtailment for all system non-synchronous penetration limits considered. However, as installed capacity of renewables grows the volume of generation curtailed also increases with a disproportionate volume occurring at weekends. The total volume of curtailment is highly dependent on ratio of wind and solar capacity, with the current blend close to the optimum level