Hanna Ryan, Marqusee Jeffrey
Center for Energy Research, University of California San Diego, La Jolla, CA 92093, USA.
Deep Decarbonization Initiative, University of California San Diego, La Jolla, CA 92093, USA.
iScience. 2021 Dec 11;25(1):103630. doi: 10.1016/j.isci.2021.103630. eCollection 2022 Jan 21.
Mitigating and adapting to climate change requires decarbonizing electricity while ensuring resilience of supply, since a warming planet will lead to greater extremes in weather and, plausibly, in power outages. Although it is well known that long-duration outages severely impact economies, such outages are usually not well characterized or modeled in grid infrastructure planning tools. Here, we bring together data and modeling techniques and show how they can be used to characterize and model long-duration outages. We illustrate how to integrate outages in planning tools for one promising mode of resilient energy supply-microgrids. Failing to treat these extremes in models can lead to microgrid designs (1) that do not realize their full value of resilience, since models do not see the benefits of protecting against extremes, and (2) that appear reliable on paper yet do not actually protect against extremes. Although utilities record power interruptions, lack of access to that data is hindering research on resilience; making datasets available publicly would substantially aid efforts to improve grid planning tools.
缓解和适应气候变化需要在确保电力供应弹性的同时实现电力脱碳，因为全球变暖将导致天气更加极端，停电情况可能也会增多。虽然众所周知，长时间停电会严重影响经济，但在电网基础设施规划工具中，此类停电通常没有得到很好的描述或建模。在这里，我们汇集了数据和建模技术，并展示了如何使用它们来描述和模拟长时间停电情况。我们说明了如何将停电情况整合到一种有前景的弹性能源供应模式——微电网的规划工具中。在模型中未能处理这些极端情况可能会导致微电网设计：（1）无法充分实现其弹性价值，因为模型看不到抵御极端情况的好处；（2）在理论上看似可靠，但实际上并不能抵御极端情况。尽管公用事业公司会记录停电情况，但无法获取这些数据阻碍了对弹性的研究；公开数据集将极大地有助于改进电网规划工具的工作。
