Smart grids concept in electrical distribution system

This paper defines key business processes in electrical distribution systems and key elements and priority components that should be (re)defined in these processes in order to enable the goals of smart grids concept to be fulfilled in the cost effective way. Activities undertaken in the Power Distribution Company of “Elektrovojvodina” (Serbia), which provide the basis for fulfilling the Smart Grids goals and thus enable full implementation of smart grids concept are presented in details

Infrastructure for collaborating data-researchers in a smart grid pilot

A large amount of stakeholders are often involved in Smart Grid projects. Each partner has its own way of storing, representing and accessing its data. An integrated data storage and a joint online analytical mining infrastructure is needed to limit the amount of duplicated work and to raise the overall security of the system. The proposed infrastructure is composed of standard application software and an in-house developed data analysis tool that allows researchers to add and share their own functionality without compromising security

Wide-Area Measurement-Driven Approaches for Power System Modeling and Analytics

This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising. Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses. Furthermore, since auto-regressive models are in a big family, the ARX model can be modified as other models for various purposes. A multi-input multi-output (MIMO) auto-regressive moving average with exogenous inputs (ARMAX) model is introduced to identify a low-order transfer function model of power systems for adaptive and coordinated damping control. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify an online measurement-based transfer function model that can be used to tune the oscillation damping controller. A demonstration on hardware testbed may illustrate the effectiveness of the proposed adaptive and coordinated damping controller. In fact, measurement-driven approaches for power system modeling and analytics are also attractive to the power industry since a huge number of monitoring devices are deployed in substations and power plants. However, most current systems for collecting and monitoring data are isolated, thereby obstructing the integration of the various data into a holistic model. To improve the capability of utilizing big data and leverage wide-area measurement-driven approaches in the power industry, this dissertation also describes a comprehensive solution through building out an enterprise-level data platform based on the PI system to support data-driven applications and analytics. One of the applications is to identify transmission-line parameters using PMU data. The identification can obtain more accurate parameters than the current parameters in PSS®E and EMS after verifying the calculation results in EMS state estimation. In addition, based on temperature information from online asset monitoring, the impact of temperature change can be observed by the variance of transmission-line resistance