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Optimal planning of integrated energy systems for offshore oil extraction and processing platforms

Zhang, Anan, Zhang, Hong, Qadrdan, Meysam, Yang, Wei, Jin, Xiaolong and Wu, Jianzhong 2019. Optimal planning of integrated energy systems for offshore oil extraction and processing platforms. Energies 12 (4) , 756. 10.3390/en12040756

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Abstract

With the introduction of new technologies, such as waste heat recovery units (WHRU), associated gas utilization, the energy flow coupling relationship is further deepened within the energy system of the offshore oil and gas production platform. Besides, the energy system is closely linked with the oil and gas production system, and a closed-loop relationship between energy flow and material flow can be revealed. Uncertainties of energy supply and production process may lead to system-wide fluctuations, which threaten the stable operation of the platform. Therefore, an optimal planning model of integrated energy system for offshore oil and gas production platform is proposed in this paper. Firstly, a generalized energy and material flow model is proposed, three matrixes are defined based on laws of thermodynamics, including energy matrix, process matrix and feedback matrix. Secondly, the energy-material conversion relationship between the energy system and production system of a typical offshore oil and gas platform is quantitatively described, together with the coupling between the input and output of the two systems. Thirdly, considering the energy-material balance constraints and the uncertainties of production system, a multi-objective stochastic planning model for the offshore integrated energy system is established, which takes economics and environmental protection into consideration. A Monte Carlo simulation-based NSGA-II algorithm is proposed to solve the model. Finally, the validity and feasibility of the proposed methodology are demonstrated through an offshore oil and gas platform in Bohai, China. Compared with the traditional planning method, the total cost and CO2 emissions of the proposed method are reduced by 18.9% and 17.3%, respectively.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: MDPI
ISSN: 1996-1073
Date of Acceptance: 21 February 2019
Last Modified: 31 May 2019 20:37
URI: http://orca.cf.ac.uk/id/eprint/121663

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