Advanced Load Modeling

俄亥俄州立大学、亚利桑那州立大学和亚利桑那公共服务公司将在电力系统负荷建模的基础研究方面进行合作研究。在未来的几十年里，由于缺乏新的输电设施，美国的电力系统将面临大容量输电能力的瓶颈。提高现有设施的利用率，以应对日益增长的大规模电力传输和第三方接入，将需要更仔细地研究系统动态性能。为了准确地研究电力系统的动态性能，需要建立准确的电力系统模型。其动机是使负荷建模精度与发电和系统建模精度相称。该项目的主要主题是利用发电机参数估计和发电机建模的先进系统识别概念进行电力系统负载建模。负荷建模的特点包括：模型的自动更新，人工神经网络模型的利用，以及在整个项目中使用实际工业数据。如果成功，这项工作将是电力系统负载自动建模的重大进步，也将显著提高动态研究的系统建模精度。因此，拟议研究的经济影响是显著的，通过增加输电能力和推迟新建设的需要，允许电力系统更接近稳定极限的运行。

The Ohio State University, Arizona State University and Arizona Public Service Company will undertake a collaborative research effort in a fundamental study on the modeling of power system loads. In the next decades, the power systems of the United States will face bottlenecks of bulk power transfer capabilities because of the virtual absence of new transmission facilities. The increased utilization of the existingfacilities to cope with growing magnitude of bulk power transfers and third-party access will require a closer look at system dynamic performance. Accurate power system models are needed for accurate study of system dynamic performance. The motivation is to make load modeling accuracy commensurate with generation and system modeling accuracy. The main theme of this project is to utilize the advanced system identification concepts developed for generator parameter estimation and generator modeling for power system load modeling. Features of the load modeling include: automatic updating of the model, utilization of an artificial neural network model, and work with actual industrial data throughout the project. If successful, the work would be a major advance in the automated load modeling of power system loads as well as a significant increase in system modeling accuracy for dynamic studies. Therefore, the economic impact of the proposed research is significant in permitting operation of power systems closer to the stability limit by increasing the transfer capabilities and postponing the need for new construction.