Climate science support for robust decision making in wind energy investments and policies
Lead Research Organisation:
University of Cambridge
Department Name: Land Economy
Abstract
The expansion of renewable energy, as part of a transition to a sustainable energy economy, has large potential to mitigate the risks associated with anthropogenic climate change. In this context, wind power is an important energy resource. The issue of public and private sector investment in wind power is a collective action problem involving a range of stakeholders, including: wind turbine companies; the National Grid; the Department of Energy and Climate Change; energy infrastructure engineers; and energy investors.
However, the wind power resource base is, by its very nature, sensitive to fluctuations in climate (Edenhofer et al. 2011). This sensitivity has implications for how the costs assumed in investment decisions evolve into the future. For instance, there may be a risk of stranded assets should wind patterns change significantly over the lifetime of a wind farm. Therefore, decision-making about the positioning of future wind turbines and investment in associated infrastructure requires information relating to wind potential patterns under different scenarios of climate change, the spatial distribution of the existing transmission network, and the decision-making criteria of key stakeholders.
There is also a degree of uncertainty associated with some of this information. While some of the uncertainties in the science can be characterised probabilistically, other sources of uncertainty (such as the global policies needed for a particular climate future to be realised) are not probabilistic by nature and so must be treated in a different way in taking investment and deployment decisions. In this context, a framework of Robust Decision-Making (RDM: Lempert, 2013) can be helpful. Rather than seeking an optimal solution, RDM provides a process for identifying strategies that remain robust across a range of potential future scenarios.
The aim of the proposed research is to build a robust decision-making tool to help stakeholders identify wind energy investments and placements of turbines or associated infrastructure that produce satisfactory performance metrics across a wide range of possible climate futures. This decision support tool would harness existing advanced climate modelling approaches and decision-making frameworks, to help stakeholders visualise the vulnerabilities and trade-offs of different positioning strategies in the energy market. Climate information will be supplied by the climate model emulator PLASIM-ENTSem (Holden et al., 2013), a sophisticated, yet computationally very fast, approach to representing the climate.
The decision-making tool would be developed, tested and evaluated with involvement from the stakeholders. As such, the tool developed would enable stakeholders to identify positioning strategies that are robust to a range of different climate change scenarios, across different Representative Concentration Pathways. In this way, the project would address the challenges of building resilience and managing climate change risks, within the wind energy sector.
Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S., Stechow, C. von and Matschoss, P.: Renewable Energy Sources and Climate Change Mitigation: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press., 2011.
Lempert, R.: Scenarios the illuminate vulnerabilities and robust responses, Climatic Change, 117, 627-646, 2013
Holden, P. B., Edwards, N. R., Garthwaite, P. H., Fraedrich, K., Lunkeit, F., Kirk, E., Labriet, M. Kanudia, A. and Babonneau, F.: PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment, Geoscientific model development discussions, 6(2), 3349-3380, 2013
However, the wind power resource base is, by its very nature, sensitive to fluctuations in climate (Edenhofer et al. 2011). This sensitivity has implications for how the costs assumed in investment decisions evolve into the future. For instance, there may be a risk of stranded assets should wind patterns change significantly over the lifetime of a wind farm. Therefore, decision-making about the positioning of future wind turbines and investment in associated infrastructure requires information relating to wind potential patterns under different scenarios of climate change, the spatial distribution of the existing transmission network, and the decision-making criteria of key stakeholders.
There is also a degree of uncertainty associated with some of this information. While some of the uncertainties in the science can be characterised probabilistically, other sources of uncertainty (such as the global policies needed for a particular climate future to be realised) are not probabilistic by nature and so must be treated in a different way in taking investment and deployment decisions. In this context, a framework of Robust Decision-Making (RDM: Lempert, 2013) can be helpful. Rather than seeking an optimal solution, RDM provides a process for identifying strategies that remain robust across a range of potential future scenarios.
The aim of the proposed research is to build a robust decision-making tool to help stakeholders identify wind energy investments and placements of turbines or associated infrastructure that produce satisfactory performance metrics across a wide range of possible climate futures. This decision support tool would harness existing advanced climate modelling approaches and decision-making frameworks, to help stakeholders visualise the vulnerabilities and trade-offs of different positioning strategies in the energy market. Climate information will be supplied by the climate model emulator PLASIM-ENTSem (Holden et al., 2013), a sophisticated, yet computationally very fast, approach to representing the climate.
The decision-making tool would be developed, tested and evaluated with involvement from the stakeholders. As such, the tool developed would enable stakeholders to identify positioning strategies that are robust to a range of different climate change scenarios, across different Representative Concentration Pathways. In this way, the project would address the challenges of building resilience and managing climate change risks, within the wind energy sector.
Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Seyboth, K., Kadner, S., Zwickel, T., Eickemeier, P., Hansen, G., Schlömer, S., Stechow, C. von and Matschoss, P.: Renewable Energy Sources and Climate Change Mitigation: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press., 2011.
Lempert, R.: Scenarios the illuminate vulnerabilities and robust responses, Climatic Change, 117, 627-646, 2013
Holden, P. B., Edwards, N. R., Garthwaite, P. H., Fraedrich, K., Lunkeit, F., Kirk, E., Labriet, M. Kanudia, A. and Babonneau, F.: PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment, Geoscientific model development discussions, 6(2), 3349-3380, 2013
Description | As expected, the wind energy industry participants were able to make use of the wind energy climate science estimates to carry forward project investments. However, an unexpected result from the workshops associated with the project was that these participants valued much more highly the detailed information n public attitudes towards wind energy, and the locations of sites where planning permission had already been granted. Hence the social information proved more valuable than the scientific information. |
Exploitation Route | They can be used to design a next generation development of a database on the suitability of project sites in the UK. |
Sectors | Energy |
Description | Our findings have been used by the wind energy industry in the UK to identify information needs to bring projects forward. |
First Year Of Impact | 2016 |
Sector | Energy |
Impact Types | Economic Policy & public services |
Description | UK Parliamentary committee on climate change |
Geographic Reach | National |
Policy Influence Type | Membership of a guideline committee |
Impact | The second climate change risk assessment has been influential in directing public funding and policies towards climate change adaptation, in part within the energy sector explored in the NERC grant. |
Description | ToPDAd |
Amount | £2,500,000 (GBP) |
Funding ID | 308620 |
Organisation | European Commission |
Department | Seventh Framework Programme (FP7) |
Sector | Public |
Country | European Union (EU) |
Start | 01/2014 |
End | 09/2016 |
Title | Reduced scale model for climate impacts on wind energy |
Description | The methodology developed allows for rapid assessment of the impacts of a changing climate on wind energy availability in the UK (the focus of this project) or globally (a possible extension) |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2016 |
Provided To Others? | Yes |
Impact | Enhanced ability of the research community to collaborate with the wind energy industry to provide information needed for selection of suitable locations for wind energy investment. |
Description | Tool assisted policy development |
Organisation | The ToPDAd project team |
Sector | Academic/University |
PI Contribution | We used the results of the NERC project to develop a wind energy case study for the ToPDAd FP7 project. |
Collaborator Contribution | Our partners provided a complementary analysis of wind energy based on their energy-economy models to assess full macroeconomic impacts of wind energy development. |
Impact | ToPDAd project reports, and presentations at 3 international meetings on climate adaptation, including the most recent COP meeting for climate change. |
Start Year | 2015 |
Description | Second UK Climate Change Risk Assessment |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | The project team were part of the expert panel put together by the CCC to develop the second climate change risk assessment for the UK. |
Year(s) Of Engagement Activity | 2016 |