碳配额场下以乙醇胺溶液进行碳捕集电厂优化竞标和运行基于强化学习SArSA 时间差分算法解决方案.pdf

Engineering 3 (2017) 257–265 Contents lists available at ScienceDirect Engineering journal homepage: /locate/eng Research Smart Process Manufacturing—Article Optimal Bidding and Operation of a Power Plant with Solvent-Based Carbon Capture under a CO2 Allowance Market: A Solution with a Reinforcement Learning-Based Sarsa Temporal-Difference Algorithm a a, b Ziang Li , Zhengtao Ding *, Meihong Wang 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 a r t i c l e i n f o a b s t r a c t Article history: In this paper, a reinforcement learning (RL)-based Sarsa temporal-difference (TD) algorithm is applied to Received 17 January 2017 search for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine Revised 2 March 2017 (MEA)-based post-combustion carbon capture under different carbon dioxide (CO2 ) allowance market con- Accepted 10 March 2017 ditions. The objective of the decision maker for the power plant is to maximize the discounted cumulative Available online 24 March 2017 profit during the power plant lifetime. Two constraints are considered for the objective formulation. Firstly, the tradeoff between the energy-intensive carbon capture and the