09-11-2012, 06:19 PM
Power Quality Analysis: a Distributed Measurement System
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INTRODUCTION
IN the new context of open electricity market, system
operators will have to report more and more to external
parties, namely to users and to regulators, about power
system performances in terms of Power Quality (PQ) issues.
Indeed, a number of regulators have already defined, or are
planning to establish, power quality objectives (supply
continuity and voltage quality) to be met by the electricity
supply systems. In some countries, regulators may even
impose penalties in case of non-observance of the power
quality objectives. The need of a distributed monitoring of PQ
indexes becomes a crucial point.
In general, with reference to PQ issues, two main aspects
are focused on: Commercial Quality and Quality of Supply;
the former concerns mainly legal and commercial interests,
such as contracts, customer satisfaction and so on, the latter
deals with more technical aspects. In this context, it is
necessary to monitor both the behavior of ''sensitive''
customers and that of ''aggressive'' customers contributing to
PQ degradation.
The information acquired by PQ monitoring systems, in
particular with reference to conducted disturbances, must be
stored and analyzed remotely from the measuring point. With
the widespread diffusion of computer networks and Internet,
and also thanks to the introduction of tools for distributed
monitoring systems design in the market, the trend is to built
up even more sophisticated systems.
ADVANCED INSTRUMENTS
The measurement of the above-mentioned PQ indexes can
be made with general purpose or dedicated measurement
devices. In the following the realized measurement devices are
described in detail.
A. Non-Stationary Disturbance Analyzer
The developed digital instrument implements a new method
for a real-time non-stationary disturbance analysis devoted to
transients, dips, swells and interruptions [6]. The method, fully
described in [7], represents a valid alternative to the other
methods ([8]) for a fast and accurate detection, extraction and
characterization of these disturbances. It is based on the idea
of analyzing the acquired signals in the time domain sample by
sample, utilizing both the concepts of sliding window and
variable thresholds, according to the recent standards ([5]).
The method is characterized by two fundamental properties: i)
the capability to take also into account stationary disturbances,
like at harmonic and interharmonic components, ii) the
capability to limit the synchronization error with a suitable
analysis and with a proper use of the sliding window.
The non-stationary disturbance (NSD) analyzer ([9]),
shown in Fig. 2, adopts a TMS320C6711 32-bit floating point
DSP based on the very-long-instruction-word (VLIW)
architecture [10]. The special internal memory architecture,
based on two independent memory banks, each one of 32 kB,
allows two memory accesses within one instruction cycle and
consequently a reduction of number of instructions.
ON-FIELD MONITORING
On-field monitoring were performed with reference to the
distributed monitoring system reported in Fig. 6 that reflects
the architecture proposed in Section II. It is composed of the
previously described advanced instruments and of commercial
devices located at two distinct sites. Locally, the instruments
are interconnected by a LAN and the acquired data are
transferred to a local data-web server. The communication
between the two LAN is possible by a WAN connection.
The power systems under investigation are a low voltage
system supplying the EMC Laboratory of the Second
University of Naples (SUN) and a low voltage system
supplying the Measurement Laboratory of the University of
L’Aquila (LAQ). The field monitoring devices considered are
a commercial PQ, a NSD and a TRAMS analyzer located on
SUN site and a PQ web instrument located on LAQ site. For
each site, a personal computer operating as data-web server is
utilized. On the data-web server the software to control
specific devices and the software used for post-processing
analyses (disturbance classification, statistical analysis,
graphic functions etc.) run.
CONCLUSIONS
A distributed Power Quality monitoring system that allows
analyzing all steady and non-steady state phenomena related to
Power Quality has been presented. The system is flexible and
open to changes and improvements. The monitoring system
has been presented with reference to its distributed architecture
describing the several remote measurement substations that are
based both on commercial and advanced high performance
devices. Some on-field measurements performed on two
different low voltage sub-networks have been reported for
mains Power Quality phenomena. Also some statistical
analysis results have been reported to highlight the satisfactory
performances of the proposed measurement system.