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A multi-period optimisation model for planning carbon sequestration retrofits in the electricity sector

机译:用于规划电力部门固碳改造的多周期优化模型

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Carbon capture and storage (CCS) is a low-carbon technology aiming to prevent carbon dioxide (CO2) generated in large industrial facilities (e.g. power plants) from entering the atmosphere, thus mitigating human-caused climate change. CCS is deemed to be one of the most promising approaches to reduce industrial CO2 emissions on a global scale, in addition to energy efficiency enhancement and increased use of renewables. This paper presents a mathematical programming model for multi-period planning of power plant retrofits with carbon capture (CC) technologies. The model allows for energy penalties due to CC retrofits and the need for compensatory power generation, as well as variations in technological parameters (such as electricity costs) over time. Furthermore, the model is formulated as a mixed integer linear programme (MILP), for which global optimality is guaranteed if a solution exists. Two case studies on carbon-constrained energy sector planning are presented to illustrate the proposed approach. Further analysis is carried out to examine the effect of the cost limit on the total increase in power generation cost. (C) 2017 Elsevier Ltd. All rights reserved.
机译:碳捕集与封存(CCS)是一种低碳技术,旨在防止大型工业设施(例如发电厂)中产生的二氧化碳(CO2)进入大气,从而减轻人为引起的气候变化。除了提高能源效率和增加可再生能源的使用之外,CCS被认为是在全球范围内减少工业CO2排放的最有前途的方法之一。本文提出了一种数学编程模型,用于采用碳捕获(CC)技术的电厂改造的多周期规划。该模型考虑到由于CC改造和对补偿性发电的需求以及技术参数(例如电费)随时间的变化而产生的能源罚款。此外,该模型被公式化为混合整数线性程序(MILP),如果存在解,则可以保证全局最优。提出了两个关于碳约束能源行业规划的案例研究,以说明该方法。进行了进一步的分析,以检验成本限制对发电总成本增加的影响。 (C)2017 Elsevier Ltd.保留所有权利。

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