Bi-level multi-objective programming approach for carbon emission quota allocation towards co-combustion of coal and sewage sludge

Qian Huang and Jiuping Xu

Energy, 2020, vol. 211, issue C

Abstract: As coal-fired power generation is responsible for more than 30% of total global emissions, co-combustion of coal and sewage sludge is widely used to reduce both carbon emissions and coal consumption. This paper proposes a bi-level multi-objective model for carbon emission quota allocation towards co-combustion of coal and sewage sludge under an uncertain environment. It considers the interactions between the authority and the coal-fired power plants in a leader-follower decision process, and seeks the trade-off among economic development, environmental protection and renewable energy utilization. Besides, fuzzy theory has been employed as an uncertainty modeling technique to characterize the vague and inaccurate decision-making environment. To solve the proposed complicated model, weighted sum method and KKT optimality conditions are applied to convert the model into a single-level single-objective model. A real case from Zhejiang Province, China is given to demonstrate the practicality and efficiency of the optimization model. Based on the analyses and discussion, this model provides reasonable and practical carbon emission quota allocation strategies for the authority. It is indicated that allocating greater quotas to lower carbon intensity coal-fired power plants could effectively achieve reduction targets. To verify the reasonableness, the results are compared with those of using single-level model.

Keywords: Coal; sewage sludge; Co-combustion; Carbon emission quota allocation; Bi-level multi-objective model (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:211:y:2020:i:c:s0360544220318363

DOI: 10.1016/j.energy.2020.118729

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