Climate science support for robust decision making in wind energy investments and policies

作为向可持续能源经济过渡的一部分，可再生能源的扩大在减轻与人为气候变化相关的风险方面具有很大潜力。在此背景下，风电是一种重要的能源。公共和私营部门对风力发电的投资问题是一个涉及一系列利益攸关方的集体行动问题，包括：风力涡轮机公司；国家电网；能源和气候变化部；能源基础设施工程师；以及能源投资者。然而，从本质上讲，风能资源基础对气候波动非常敏感(Edenhofer等人。2011年)。这种敏感性对投资决策中假设的成本将如何演变到未来产生影响。例如，如果风场的风力模式在整个生命周期内发生重大变化，则可能存在搁浅资产的风险。因此，有关未来风力涡轮机的定位和相关基础设施投资的决策需要与不同气候变化情景下的风能模式、现有输电网络的空间分布以及关键利益攸关方的决策标准有关的信息。其中一些信息也存在一定程度的不确定性。虽然科学中的一些不确定性可以用概率来描述，但其他不确定性来源(如实现特定气候未来所需的全球政策)本质上不是概率的，因此在做出投资和部署决策时必须以不同的方式对待。在这方面，一个强有力的决策框架(RDM：Lempert，2013)可能是有帮助的。RDM不是寻求最佳解决方案，而是提供了一个过程，用于确定在一系列潜在的未来场景中保持健壮的战略。拟议研究的目的是建立一个强大的决策工具，帮助利益相关者确定风能投资和涡轮机或相关基础设施的位置，从而在各种可能的气候未来产生令人满意的性能指标。这一决策支持工具将利用现有的先进气候建模方法和决策框架，帮助利益攸关方直观地了解能源市场不同定位战略的脆弱性和权衡。气候信息将由气候模型模拟器PLASIM-ENTSem(Holden等人，2013年)提供，这是一种复杂但计算速度非常快的气候模拟方法。将在利益攸关方的参与下开发、测试和评估决策工具。因此，开发的工具将使利益攸关方能够确定在不同的代表集中途径上，对一系列不同的气候变化情景具有强大生命力的定位战略。Edenhofer，O.，Pichs-Madruga，R.，Sokona，Y.，Seybus，K.，Kadner，S.，Zwickel，T.，Eickemeier，P.，Hansen，G.，Schlömer，S.，Stecow，C.von and Matschoss，P.：可再生能源与气候变化缓解：政府间气候变化专门委员会特别报告，剑桥大学出版社，2011.Lempert，R.：阐明脆弱性和稳健应对，气候变化，117,627-646,2013Holden，P.P.B.，Edwards，N.R.，Garthwaite，P.H.，Fraedrich，K.，Lumkeit，F.，Kirk，E.，Labriet，M.Kanudia，A.和Babonneau，F.：PLASIM-ENTSem：用于影响评估的未来气候变化的时空模拟器，地球科学模型发展讨论，6(2)，3349-3380,2013

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, 2013Holden, 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