“20th PSCC 2018 papers submission and review platform

Full Program »

Probabilistic Low Voltage State Estimation using Analog-Search Techniques

Power systems are becoming more complex and the need for increased awareness at the lower voltage levels of the distribution network requires new tools that provide a reliable and accurate global image of the system. This paper describes an innovative state estimation approach for Low-Voltage (LV) networks that searches for similarities between a real-time snapshot comprising only a subset of smart meters with real-time communication, and complete system states present in historical data. Real-time voltage magnitudes are then obtained smoothing the most alike past snapshots with a methodology that do not resorts to full knowledge about network topology and characteristics. Moreover, the state estimation results will express the conditional uncertainty involved, in the form of a set of quantiles, using Kernel Density Estimation methods. The results show impressive low estimation errors, even in the scenario of strong penetration of microgeneration.

Author(s):

Gil Sampaio    
INESC TEC / Faculty of Engineering of University of Porto
Portugal

Ricardo Bessa    
INESC TEC
Portugal

Jorge Pereira    
INESC TEC / Faculty of Economics of University of Porto
Portugal

Vladimiro Miranda    
INESC TEC / Faculty of Engineering of University of Porto
Portugal

 

Powered by OpenConf®
Copyright ©2002-2014 Zakon Group LLC