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油田配电网损耗影响因素仿真分析 被引量:1

Loss Influence Factor Simulation Analysis of Oil Field Distribution Network
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摘要 油田配电网大多呈辐射状且分支较多,拓扑结构复杂,而且采油设备运行具有周期往复运行的特点,线路潮流存在一定的波动性,导致网损率普遍高于公用配电网。本文结合具体油田配电网拓扑结构与设备参数,并考虑油田负荷运行特点,系统分析了功率因数、电压等级、线路老化、变压器型号等因素对于网络损耗的影响机理;结合实际情况,基于Matlab建模仿真对比分析了针对不同影响因素的降损措施节能空间。为准确掌握油田配电网的网损影响主控因素并实施科学有效的降损措施,提供了理论支撑。 Oil field distribution networks are mostly radial with many branches and the topological structure is much complex.Meanwhile,the oilfield load usually works with cycling characteristics and power flow in the distribution network is with high fluctuation.The network loss rate is generally higher than that of public distribution network.In this paper,combined with the specific oil field distribution network topology and equipment parameters,and the characteristics of oilfield load operation,influence mechanism of some factors is systematically analyzed.The influence elements on the network loss are considered with the actual field situation,such as power factor,voltage level,line aging,transformer model,etc.Based on Matlab modeling and simulation,the energy-saving space of loss reduction measures for different influencing factors is compared and analyzed.It provides theoretical support for accurately grasping the main control factors of the oil field distribution network loss and implementing scientific and effective loss reduction measures.
作者 王浩 刘军 严川 李炜 石小满 仉志华 WANG Hao;LIU Jun;YAN Chuan;LI Wei;SHI Xiao-man;ZHANG Zhi-hua(College of New Energy of China University of Petroleum,Qingdao 266580,China;Shengli Petroleum Administration Bureau,SINOPEC,Dongying 257000,China;Operation Management Office,Shengli Petroleum Administration Bureau,SINOPEC,Dongying 257000,China;Technical Testing Center,Shengli Oilfield Sub-company,SINOPEC,Dongying 257000,China;Gudong Oil Production Plant,Shengli Oilfield Sub-company,SINOPEC,Dongying 257237,China)
出处 《节能技术》 CAS 2021年第6期527-532,共6页 Energy Conservation Technology
基金 中石化重点科技攻关项目(319020-7)。
关键词 油田配电网 网络损耗 影响因素 降损策略 仿真分析 oil field distribution network network loss influence factors loss reduction measures simulation analysis
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