PMU Applications for Distribution Networks (DN)

 

This project aims at exploiting the applications of Phasor Measurement Units (PMUs) in distribution networks. The integration of volatile and distributed generation (DG), the arising of dual load-generator behavior of the end users, and the presence of new technologies and services, make the distribution networks more dynamic and complex. The arising challenges in energy management and control can be addressed through the use of synchrophasor measurements and real time monitoring, state estimation and stability analysis.

  Copyright: © RWTH Aachen Measurement infrastructure and current operation of a distribution network

The deployment of photovoltaic (PV) power generation in distribution has led to an exacerbation of unbalanced operating

conditions, which, in turn, has increased the challenge of operating the distribution network in Bavaria efficiently and safely. Furthermore, due to the uncertainty caused by the variability of renewable sources and to the extensive use of pseudo measurements caused by a lack of a pervasive measurement infrastructure, the dynamics and uncertainty of operation of the distribution network may not be neglected.

Situation awareness is a primary need to address all these challenges. This is achieved by determining the requirements

and characteristics of the measurement infrastructure and developing applications, in particular state estimation, that are fit for the needs and characteristics of the distribution system and exploit at best the measurement infrastructure.

Regarding the measurement infrastructure, we investigate the optimal placement of the new measuring devices (mainly PMUs) to ensure observability of the whole network and robustness to loss of instruments and communication, to minimize the uncertainty of the state estimates and the total cost. Besides the deployment of PMU and classical instrumentation, we also consider the integration of other existing information in the current network, e.g. data from smart meters (SM). In addition, different network topologies and variable operating conditions, such as uncertain behavior of load and renewable generation, over the time, are also taken into account in the optimal placement.“

Regarding distribution state estimation (DSE), we are investigating the adoption of hypothesis and simplifying assumptions,

which are different from the transmission system case, and we are developing a state estimator with a three-phase formalization to track the unbalance feature. Finally, we are looking at the real world requirements for dynamic state tracking and the sustainable ways to implement it. This aims at supporting frequency and voltage stability assessment and control.

This work is carried out in cooperation with Prof. Carlo Muscas, at the University of Cagliari, Italy.