Research on the key issues in energy efficiency evaluation and improvement of offshore micro-integrated energy systems

doi:10.3969/j.issn.1674-1951.2021.04.004

Abstract

Abstract:

At present,the worldwide energy crisis is increasingly intractable.Energy is the key factor restricting the development of every country.Oceans occupies vast area and are of rich and diverse resources,which provide a breakthrough for solving the energy crisis.Offshore oil attracts more attention as onshore oil is drying up.The offshore oil and gas platform is the key to offshore oil utilization.For lack of research on the specific integrated energy system,it is an urgent issue to make the platform run efficiently.Focusing on the integrated energy management technology of offshore oil and gas platforms,the energy consumption characteristics and load forecasting methods of the platform are summed up.Then a comprehensive energy consumption modelling method for the system interconnected multiple offshore platforms is put forward.Energy efficiency evaluation index and method for offshore oil platforms can quantify the efficiency of the platform.Combining the technologies that can improve the energy efficiency of the platform with the proposed evaluation methods,the research provides new concept for improving the energy efficiency of offshore oil platforms in China.

Key words: offshore oil and gas platform, load forecasting, comprehensive energy consumption modeling, evaluation of energy efficiency, energy efficiency improvement method, integrated energy systems

CLC Number:

TK01⁺8

XU Shihua, LIU Ping, QIU Rui, OUYANG Jun, KONG Fanxu, XU Bin, ZHANG Junbo, WU Jun, HAN Rui. Research on the key issues in energy efficiency evaluation and improvement of offshore micro-integrated energy systems[J]. Huadian Technology, 2021, 43(4): 21-27.

Figures/Tables 7

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电负荷分类	负荷特点	预测方法
油田整体电负荷	设备种类多,影响因素复杂,难以通过数学建模机理描述	人工神经网络,并与预测天然气负荷进行耦合校验
中心平台/综合平台电负荷	通常为产出物的集中处理平台,影响因素复杂,难以通过数学建模机理描述
井口平台电负荷	影响因素较少,但电潜泵负荷数学建模机理复杂,本身负荷影响因素多

天然气负荷分类	负荷特点	预测方法
电站负荷	与发电量及电站负荷率密切相关,影响因素相对较少	多元线性回归法、人工神经网络混合算法,并与预测电负荷进行耦合校验
锅炉负荷	与本单元热负荷及废热锅炉运行状态密切相关,影响因素相对较少
其他负荷	占比较少
外输天然气	受下游用户影响,影响因数复杂,随机性大	人工神经网络