Smart Cities / Smart Grids


i-PQM: Intelligent monitoring of the electric energy quality

i-PQM is the follow-up to the project "Model-based and case-based power distribution network diagnose" (reference DPI 2006-09370), which  focused on the analysis of single disturbances registered in power distribution networks for fault diagnosis purposes. Assuming that disturbances propagate through the network following electric laws, it seems feasible to exploit this redundancy (the same disturbance is registered by multiple monitors) to reduce uncertainty and increase coverage and soundness of power quality monitoring systems. In a similar way, the analysis of sequences of disturbances is crucial to define prediction models necessary to assist the maintenance polices.

The aim of this project is to build an intelligent power quality monitoring framework to exploit temporal and spatial correlation of disturbances gathered in multiple monitoring points around the power network to assist maintenance polices. Partial objectives of the project cover the application of data mining strategies to discover sequence patterns useful for the improvement of fault location methods and prognosis of incipient faults in the distribution network; and also the exploitation of spatial correlation of data registered by multiple power quality registers scattered around the power network.

The combination of sequence pattern analysis methods (knowledge discovery and recognition) with fault location methods will improve the efficiency in fault location and forecasting; whereas the definition of similarity criteria among substations (topology, power installed) and correlation analysis (temporal consistency and spatial correlation) are proposed to estimate and assess power quality of other not measured points.

A multi-agent conception of the whole system and the agentification of power quality monitors are proposed to achieve modularity and flexibility of the proposed framework. The shift in the use of power quality monitoring system from a traditional data acquisition system to a fully automated intelligent analysis system will increase the value of power quality monitoring. This implies the inclusion of intelligent capabilities to the power quality monitoring and the communication among other power quality agents in the system to increase soundness and coverage of the power quality monitoring system.


Start: 01/01/2010

End: 31/12/2012

Funder: MICINN

Grant: € 114,950

IIiA Coordinator: Joaquim Meléndez