A Comprehensive Approach to Monitoring Active Distribution Systems

该项目旨在促进下一代主动配电系统的高效和可靠运行。 这将通过改进监测、控制和优化其运作来实现。总体影响将是向最终用户提供更可靠、成本更低和环境更清洁的能源。 此外，该项目成果的实施和利用将为该国下一代电力工程师提供就业和培训机会。 该项目的智力优势包括通过检测测量和网络模型误差来提高使用网络模型的网络应用程序的可靠性;使用新的补偿和校准方法，使系统的运行状态无偏跟踪;促进可再生能源在大型电网的整体发电调度中的结合。 该项目的更广泛影响包括通过夏季REU项目对代表性不足和少数群体的学生进行培训和教育，并在常规学期担任学生研究员;以及改造未来配电系统的监控和操作，使其更加可靠。该项目的目标是应对未来配电系统监控方面的挑战。 配电系统一直被孤立地对待，直到最近，然而，由于可再生能源，非传统负载和储能设施在配电和输电系统之间产生双向功率流，近年来配电系统的组成和所需的分析工具发生了巨大变化。因此，这些系统的有效管理需要对状态、拓扑和模型参数进行可靠和有效的监控。 因此，该项目全面调查了混合相配电系统的监测挑战，包括不同类型的测量，非径向配置，以及测量和网络模型参数的误差。 详细的数学公式用于混合相配电系统状态估计，其利用模态分解、用于混合相网络模型的基于拉格朗日的参数误差检测方法的扩展、线路模型的动态跟踪以及解码它们以检测和定位不同类型的故障和扰动;三相同步相量测量的远程校准和通过递归多路复用定位拓扑误差，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to facilitate efficient and reliable operation of next generation active distribution systems. This will be accomplished by improved monitoring, control and optimization of their operation. The overall impact will be more reliable, less costly and environmentally cleaner energy delivery to the end users. Furthermore, implementation and utilization of the project’s results will provide job and training opportunities for the next generation of power engineers in the nation. The intellectual merits of the project include improved reliability of network applications that use the network model, by detecting both measurement and network model errors; using novel compensation and calibration methods that enable unbiased tracking of the system’s operating states; and facilitating incorporation of renewable energy sources in overall generation dispatch of large power grids. The broader impacts of the project include training and education of students from underrepresented and minority groups via REU programs in the summers and as student researchers during regular semesters; and transformation of the monitoring and operation of future distribution systems making them more reliable.The goal of the project is to address challenges in monitoring future distribution systems. Distribution systems have been treated in isolation until recently, however their composition and required analysis tools have drastically changed in the recent years due to the renewable energy sources, non-conventional loads, and energy storage facilities creating bi-directional power flows between distribution and transmission systems. Thus, effective management of these systems requires reliable and efficient monitoring of the state, topology and model parameters. Thus, the project comprehensively investigates the monitoring challenges for mixed-phase distribution systems containing different types of measurements, non-radial configurations, and errors in both measurements and network model parameters. Detailed mathematical formulation for mixed phase distribution system state estimation which exploits modal decomposition, extension of Lagrangian based parameter error detection method for mixed-phase network models, dynamic tracking of line model and decoding them to detect and locate different types of faults and disturbances; remote calibration of three phase synchronized phasor measurements and localizing topology errors by recursive multi-area estimation constitute the technical innovations associated with the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.