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抽油机电动机(beam pumping motor,BPM)负荷具有周期性动态变化特点,对于此类工况下的电动机能效检测通常采用标准井测试方法,该方法存在负载单一、通用性差等局限性,难以灵活地模拟油田复杂的负荷特性。为解决这一问题,以国内外油田广泛应用的游梁式抽油机为例,建立了抽油机系统(beam pumping system,BPS)数学模型并分析了模型参数对仿真误差的影响;在此基础上,提出一种通过调整平衡配重及井下摩擦力参数值大小来补偿模型误差的技术手段,并通过遗传算法(genetic algorithms,GA)对上述参数进行优化求解;进一步基于该模型开发出一套室内BPM模拟加载测试系统,该系统采用由四象限变频器与伺服电机组成的能量回馈式单元作负载,仅通过改变上位机BPS模型参数便可实现不同动态负荷的精确模拟。与现场测试结果对比表明,该系统可模拟抽油机空载、轻载及重载工况下的动态负荷特性,误差低于2%,系统节电率达87%。文中研究成果可为油田电机选型及能效动态评估提供重要技术支持。
The load of the beam pumping motor (BPM) has the characteristics of periodic dynamic changes. For the efficiency testing of motor under such conditions, the standard well testing method is usually adopted. This method has the limitations of single load and poor universality, which makes it difficult to be flexible To simulate the complex load characteristics of oilfields. In order to solve this problem, a beam pumping system (BPS) mathematical model is established and the effect of model parameters on the simulation error is analyzed, taking the beam pumping unit widely used in domestic and overseas oilfields as an example. Based on the proposed method, a technical method of compensating model errors by adjusting balance weight and downhole friction parameter values is proposed, and the above parameters are optimized and solved by using genetic algorithms (GA). Based on the model, a The indoor BPM simulation load test system uses a four-quadrant inverter and servo motor energy feedback unit as a load, only by changing the host computer BPS model parameters can be accurately simulated different dynamic load. The comparison with the field test results shows that the system can simulate the dynamic load characteristics of the pumping unit under no-load, light-load and heavy-load conditions with the error less than 2% and the system saving rate of 87%. The research results in this paper can provide important technical support for oil field motor selection and energy efficiency dynamic assessment.