Multi-objective optimal scheduling of offshore micro integrated energy system considering natural gas emission. (February 2021)

• Record Type: Journal Article
• Authors: Wu, Jun; Li, Baolin; Chen, Jun; Ding, Yurong; Lou, Qinghui; Xing, Xiangyu; Gan, Peiying; Zhou, Hui; Chen, Junfeng
• Is Part Of: International journal of electrical power & energy systems. Volume 125(2021)
• Publication Date: 2021-02
• Subjects: Offshore micro integrated energy system -- Multi-objective optimization -- NSGAII -- Natural gas emission -- Comprehensive energy efficiency; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2020.106535
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Summarizing the features of OOGE as well as the differences between OMIES and IES. Proposing a bi-objective optimal economical/environmental model of OMIES. The CDP used in NSGAII was improved to handle various constraints efficiently. Influences of scheduling solutions were discussed, including natural gas emission. Abstract: Offshore oil and gas engineering (OOGE) refers to the offshore micro integrated energy system (OMIES) that purposes to exploit the primary energy and integrates the production, transmission, and consumption of energy. Currently, natural gas emission in OMIES has caused extra energy waste and environmental pollution. To reduce natural gas emission and improve the operating economy of OMIES, a bi-objective optimal scheduling model of OMIES is proposed in this paper, considering the overall operating cost(including the penalty cost of natural gas emission) as well as the operating state of the gas turbine generator units (GTGUs). The non-dominated sorting genetic algorithm II (NSGAII) is introduced to solve this multi-objective optimization problem. And the constraint domination principle (CDP) is improved to handle all kinds of constraints involved in the mathematical model. Finally, an OMIES in the Bohai Sea is utilized as an example and the efficiency of the solution method, as well as the validity and feasibility of the proposed model in improving the economy and efficiency of OMIES, are verified.