Energy sector encompasses all activities related to generation and distribution of energy.
Security and efficiency of energy infrastructures is critical for our societies and economies. Energy constitutes a diverse sector with a wide range of stakeholders and potential needs for climate information. Three key themes/cases are identified: (i) electricity system, (ii) high impact events affecting the broader energy sector, and (iii) wind power resource characterization.
Electricity (power system)
In response to climate change, many European countries are sourcing an increasing fraction of their electricity from renewables such as solar, wind and hydro-power. Unlike in the case of the traditional model of power system operation, whereby the output from large power stations is directly controlled to meet electricity demand, here neither demand nor supply are known in advance. The physical and economic integration of “variable” renewable generators into power networks remains a major challenge in energy policy and planning.
Power systems pose several major scientific challenges in terms of climate modelling:
Spatial localisation. Renewable generation assets (e.g., wind- and solar farms) and demand centres (e.g., cities) exist in specific geographical locations. High-resolution climate data may therefore prove valuable in accurately assessing the climate-response of individual assets (e.g., the output from a particular wind-farm).
High-frequency time dependencies. The parts of a power system with controllable output (typically coal, gas and nuclear power plant) differ greatly in cost and response time (e.g., a typical coal power station requires several hours to "switch on" from a cold start). Accurately representing local meteorological properties at short (~0.5-3h) time scales is therefore an important ingredient in simulating power system responses.
Spatial connections and compound meteorological sensitivities. Transmission infrastructure connects the power system across national and continental scales. This, coupled with the requirement for near-instantaneous supply-demand balance across the network leads to complex multi-variate meteorological sensitivities spanning large geographical areas. The spatial correlations within and between meteorological variables therefore become very important for assessing impacts on power systems.
High impact – low probability events
Extreme weather and climate conditions have profound implications for the energy sector across a wide range of technologies and energy-forms. Some examples include:
- Cold winter temperatures: icing of power lines (leading to damage) and peaks in demand (e.g., for heating and electricity, often associated with price spikes or supply shortages).
- High summer temperatures: reduction of generation efficiency, curtailment of power plants (e.g., water used for cooling may exceed environmental regulations on temperatures for river discharge), peaks in demand (for air conditioning, often associated with price spikes or supply shortages).
- Extreme precipitation: flooding of infrastructure assets
- Drought: restrictions to hydropower availability, falling river levels limiting transport of raw fuel for electricity generation (e.g., the movement of coal on the River Rhine)
- Storm surge: risk to coastal plant (particularly nuclear)
- Extreme winds: infrastructure damage (e.g., power lines, wind farms, offshore oil rigs).
Correlations between meteorological variables and across spatial scales can play a major role. For example:
- Capacity Adequacy (for electricity): this is typically the maximum residual demand for power once the contribution from renewable generation has been deducted. It is therefore strongly dependent on both temperature (as a major driver of demand) and wind/insolation (as major drivers of renewable generation).
- Trading (for gas): the demand for gas in both the East Coast of the US and Europe is strongly linked to winter temperatures. Trans-Atlantic shipment of LNG (Liquefied natural gas) is therefore strongly influenced by temperature co-variability across the two regions.
A flexible energy sector, that incorporates electricity production from broad variety of resources, including wind energy, needs to be adaptable to changing trends in resources availability. Wind power resource characterisation and response of wind power resources to climate change is an important application of climate information in this sector. More accurate planning and resource modelling can make banks more comfortable with the risk profile of e.g. offshore wind projects and as a result, banks may increase their amount of lending to the wind energy projects. This can accelerate the pace of the offshore wind development.
High resolution Global Climate Models (GCMs) data offers advantages for both finer spatial information and enhanced physical process representation. Key concern in PRIMAVERA is to address the extent to which high-resolution GCMs provide an improvement over coarse-grain GCMs and limited area Regional Climate Models for:
- The representation of climate inputs for power system simulation (i.e., the spatial and temporal representation of temperature, wind, solar and precipitation and their co-variability).
- The underlying processes driving meteorological impacts in the energy sector (particularly large-scale teleconnections influencing the European, eddy-driven jet variability, storms and blocking).
In general, awareness and understanding of climate impacts on the energy sector remains relatively low. Specific users, and use cases, are therefore expected to be identified and developed over the course of the PRIMAVERA project. We will collaborate with and build upon a wider body of work and existing stakeholder contacts established in previous projects and the EU COPERNICUS climate services for energy. It is expected that the case studies will demonstrate a mixture of both "acute" and "chronic" impacts of climate on the energy sector across a variety of energy vectors (electricity, gas, oil).
In addition to directly approaching stakeholders (transmission system operators, investors, policy makers, and system planners), PRIMAVERA will also target an intermediary community in “energy-systems research”. This will include academic and industrial research organisations who are active in modelling and understanding the future evolution of the energy system. It is believed that this more indirect approach will enable PRIMAVERA establishing firmer links between climate and energy-research, translating PRIMAVERA science into a form more familiar to the energy community.