To decarbonize electricity grids, CO₂ capture and renewable wind/solar are two promising pathways. However, the intermittency of these variable renewable sources and the high energy requirement of carbon capture restrict their widespread deployment. These challenges are traditionally addressed independently at the grid-level, leading to conservative costs and limited operational flexibility for both systems. Here, we examine the synergistic integration of renewables and flexible carbon capture with individual fossil power plants. Renewables provide clean energy for carbon capture, while flexible carbon capture acts as a form of energy storage to counter renewable intermittency. To assess whether the benefits obtained from integration outweigh the capital cost under spatiotemporal variability of electricity markets and renewable energy, we develop a mathematical programming-based optimization framework. We decouple the design and operational decisions in a two-stage optimization strategy to efficiently solve the large-scale problem. When applied to a nationwide case study on coal plants across the US, we observe that, for futuristic carbon tax and renewable cost scenarios, it is profitable to invest in solar-assisted carbon capture for nearly one-third of the coal plants. It reduces carbon capture cost by 8.9%, and accommodates solar intermittency while avoiding the capital cost of an equivalent battery, which is 4.4 times the solar farm cost. Furthermore, the levelized cost of electricity will be less than that of new natural gas plants with overall emission reduction between 87.5 and 91%. The integrated system thereby provides a cost-effective and sustainable measure to reduce CO₂ emissions and improve the operational flexibility of existing fossil-based systems for accelerating the clean energy transition of the global energy sector.

中文翻译：

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可再生集成的灵活碳捕集：通向清洁能源未来的协同之路

为了使电网脱碳，CO ₂捕获和可再生风能/太阳能是两个有希望的途径。但是，这些可变的可再生资源的间歇性和碳捕集的高能耗要求限制了它们的广泛应用。传统上，这些挑战是在网格级别独立解决的，从而导致保守的成本和两个系统的有限的操作灵活性。在这里，我们研究了可再生能源和灵活的碳捕集与各个化石电厂的协同整合。可再生能源为碳捕集提供了清洁能源，而灵活的碳捕集则作为一种能量存储形式来应对可再生能源的间歇性。为了评估在电力市场和可再生能源的时空变化下，整合带来的收益是否超过了资本成本，我们开发了一个基于数学编程的优化框架。我们采用两阶段优化策略将设计和运营决策脱钩，以有效解决大规模问题。当将其应用于美国全国燃煤电厂的全国性案例研究时，我们观察到，对于未来的碳税和可再生成本情景而言，对近三分之一的燃煤电厂进行太阳能辅助碳捕获进行投资是有利可图的。它减少了8.9％的碳捕获成本，并适应了太阳能的间歇性，同时避免了等效电池的资本成本，后者是太阳能发电场成本的4.4倍。此外，总的减排量将在87.5％至91％之间，这将使新的天然气工厂的平均电费成本更低。₂排放，并提高了现有化石系统的运营灵活性，以加速全球能源行业的清洁能源转型。