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《工程(英文)》 >> 2017年 第3卷 第2期 doi: 10.1016/J.ENG.2017.02.014

碳配额市场下以乙醇胺溶液进行碳捕集的电厂的优化竞标和运行:基于强化学习的Sarsa时间差分算法的解决

a School of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK
b Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield S1 3JD, UK

收稿日期: 2017-01-17 修回日期: 2017-03-02 录用日期: 2017-03-10 发布日期: 2017-03-24

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摘要

对于处在碳配额市场条件下以乙醇胺(MEA) 进行碳捕集的燃煤电厂,本文应用了基于强化学习的Sarsa 时间差分算法为其自行搜寻一种统一的竞标和运行策略。电厂的决策者的目的被定义为最大化电厂寿命下的贴现累计利润。其中,我们引入以下两个限制条件:一是碳捕集的高能耗和电力生产之间的权衡;二是碳排放交易市场中竞得的碳配额数量与电力生产导致的实际碳排放量的近似相等。本文给出了三个案例方便研究。第一个案例中,我们展示了Sarsa 算法将收敛到一个确定且优化的竞标和运行策略。第二个案例中,相互独立设计的运行和竞标策略与统一设计的运行和竞标策略相互比较,以表明加入了随时间变化、市场导向的碳捕集水平后,Sarsa 算法将有助于电厂决策者获得更高的贴现累计利润。第三个案例则引入了处在同一碳配额市场的另一电厂作为原电厂的竞争对手。两家电厂设置了相同的发电和二氧化碳捕集设备,但新电厂采用不同的策略获得利润。比较两家电厂的贴现累计利润,结果表明:采用Sarsa 学习算法、找到统一的竞标和运行策略的原电厂会更具竞争力。

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