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An efficient algorithm for bi-objective combined heat and power production planning under the emission trading scheme

机译:排污权交易下双目标热电联产计划的高效算法

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摘要

The growing environmental awareness and the apparent conflicts between economic and environmental objectives turn energy planning problems naturally into multi-objective optimization problems. In the current study, mixed fuel combustion is considered as an option to achieve tradeoff between economic objective (associated with fuel cost) and emission objective (measured in CO_2 emission cost according to fuels and emission allowance price) because a fuel with higher emissions is usually cheaper than one with lower emissions. Combined heat and power (CHP) production is an important high-efficiency technology to promote under the emission trading scheme. In CHP production, the production planning of both commodities must be done in coordination. A long-term planning problem decomposes into thousands of hourly subproblems. In this paper, a bi-objective multi-period linear programming CHP planning model is presented first. Then, an efficient specialized merging algorithm for constructing the exact Pareto frontier (PF) of the problem is presented. The algorithm is theoretically and empirically compared against a modified dichotomic search algorithm. The efficiency and effectiveness of the algorithm is justified.
机译:日益增长的环境意识以及经济与环境目标之间的明显矛盾使能源规划问题自然地变成了多目标优化问题。在当前的研究中,混合燃料燃烧被视为实现经济目标(与燃料成本相关)和排放目标(根据燃料和排放配额价格以CO_2排放成本衡量)之间权衡的一种选择,因为通常排放量较高的燃料通常比低排放的便宜。热电联产是在排放交易计划下推广的一项重要的高效技术。在热电联产生产中,两种商品的生产计划必须协调进行。长期的计划问题分解为成千上万小时的子问题。本文首先提出了一种双目标多周期线性规划CHP规划模型。然后,提出了一种有效的专业合并算法,用于构造问题的精确帕累托边界(PF)。该算法在理论上和经验上都与改进的二分搜索算法进行了比较。该算法的效率和有效性是合理的。

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