The correct understanding of the applications from an offline perspective will go on to inform the processes or procedures for online applications.
2.4.2.1 Wide Area Monitoring
The ability to monitor, in real-time, synchronised power system parameters al- lows network operators a greater deal of visibility of evolving network conditions.
However, this becomes a subject for appropriate visualisation tools [55], as just
providing operators with graphs changing at high frequency would potentially just be a distraction or seen as information clutter.
The ability of WAMS to directly measure the phase angle differences around the power system, provides system operators with the ability to monitor the real time power transfer stress on various areas of the transmission system. This can help to build confidence when managing critical transmission corridors potentially al- lowing systems to be operated closer to their designed limits. This information
is particularly useful in large interconnected systems when the knowledge of a neighbouring interconnections system state is key to managing your own network. Following the blackout in the North East America and Canada in August 2003 it was deemed necessary to install a WAMS network for all regional transmission
operators, to provide a more wide area view of emerging system conditions [56].
The practical application of wide area monitoring was first realised following data collected in Texas, America in July 1993 for the Comanche Peak load rejection test
[50]. The frequency oscillations collected by PMUs revealed an electromechanical
wave propagating through the system that was easily observed in the frequency measurements. This and similar measurements in other parts of America even-
tually led to the development of a frequency monitoring network, FNET [57],
which through the installation of synchronised frequency disturbance recorders (FDR) throughout North America, provides a contour plot of frequency differ- ences throughout North America. The system also uses a triangulation method based on the travelling wave of system events to determine the approximate source of an event or incident in the network.
On a large interconnected system like North America, with very long transmission distances, this sort of information is incredibly useful to network operators allow- ing them to forecast incipient system breakups and speed up remedial actions. The application to smaller heavily meshed systems such as that of GB is less ap- parent in real-time, as the system frequency is completely synchronised around the network during the steady-state. However, with increased integration with mainland Europe and the Nordic countries, pan-European integration of real-time frequency information may become vital.
2.4.2.2 Monitoring of Inter-Area Oscillations
In an interconnected power system inter-area oscillations typically exist across weak interconnections, where generators on one side of the interconnection swing against generators on the other side. The frequencies of such inter-area modes
incapable of monitoring them, due to their network scan rates at around 4 - 10 seconds. The lack of synchronised data means an accurate picture of the shape of the modes cannot be established.
The addition of PMUs to the power system provides an enhanced level of monitor- ing for the oscillations in real-time, with accurate pictures of the mode shapes in terms of relative phase and percentage damping now able to be established online. Initial analysis takes place offline to establish the shape of a specific mode; the damping of the identified modes is then monitored closely in real-time as well as the amplitude and frequency.
Power system oscillations once observed can be damped through control systems however, it is through faults or excessive variations in generation or demand that cause this damping to break down. This needs to be monitored closely.
The GB system at present has as an inter-area mode at around 0.5Hz [13] that
is typically well damped through installed PSS’s, in addition to two other modes,
which have been identified [59], with an unstable mode at around 0.83Hz and an
inter-area mode at 0.7Hz that can be quite lightly damped. With huge changes due to impact the power system in terms of generation fleet, variability of supply and hence power flows, the damping of these modes is far less guaranteed. In addition, the drastic changes around the network could also give rise to additional
modes previously unaccounted for. The increasing number of technologies on
the system and competing control systems could mean that this phenomena will become increasingly complicated to predict and model.
2.4.2.3 Dynamic Line Ratings
The maximum power transfer capable along an overhead transmission line (am- pacity) is defined ultimately by its thermal limit, defined by the performance of the lines conductor at increasing temperatures. This is not a constant value and depends on the weather conditions, namely ambient temperature, solar radiation
and wind velocity applicable to the line. It is understood that this is most often taken as a very conservative value implying under utilisation of system assets. With a PMU installed at either end of a transmission line the synchronized phasor measurements facilitate the calculation of the lines true resistance. This informa- tion combined with knowledge of the type and length of the conductor allows the true rating of the line to be determined. The application is expected to increase asset utilization and operating efficiency.
2.4.2.4 Improved State Estimation
Wide area measurements were originally introduced as inputs for static state es- timators, designed to assess system security from the point of view of the next
contingency [22]. The measurement systems had to be designed to provide the
best “quasi-steady state” approximation of the state of the power system.
Today State Estimation (SE) is seen one of the most important applications of the Energy Management System (EMS) providing operational security assessments and contingency analysis. The goal of SE is to provide the system state, in the positive sequence voltage values (magnitude and phase), for every bus of the sys-
tem [22, 60]. This is achieved using the network model and typically a weighted
least squares technique based on redundant data in the system [25]. This is a
non-linear problem and it can take a relativley long time to converge a solution. The inclusion of PMUs to the transmission system can greatly improve both the accuracy and speed of the SE solution, with the state of the network being di-
rectly measured as opposed to estimated [22]. Hybrid State Estimators, as shown
in Figure2.6can either comprise a two-stage estimation approach, wherby the syn-
chronised measurements are combined after the conventional SE or as a combined
non-linear estimator at the start of the process [25,61].
In addition, an advanced application dealing with the provision of synchronised
phasor measurements to dynamic state estimation is explored in [62]; a Unscented
State Estimator Pn P4 P3 P2 P1 V, I, P, Q t = 0 Synchrophasor Measurements Non-Linear State Estimator Linear Conventional Measurements (a) (b)
Figure 2.6: Hybrid State Estimation (a) two-stage estimation and (b) con- ventional non-linear estimator
challenges posed from highly non-linear mathematical models of network equa- tions, usually approximated through a linearisation.