Fast on-line voltage security monitoring using synchronized phasor measurements and decision trees

Abstract

This paper presents the results of a study for an on-line voltage security monitoring system in AEP. It is designed to work inside the control center with phasor measurement units (PMUS) providing the synchronized real-time measurements. Classification type decision tree (DT) models are utilized to predict voltage security status. Fast and direct measurement from PMUS combined with decision trees quickly assessesvoltage security, leaving more time for corrective or preventive actions. Two attributes are considered in the decision tree models: generator vars and angular difference. Both are observed to be good indicators of voltage security status. The paper focuses on the angle difference atb-ibutes because bus voltage angle is directly measured by the PMUS. A stressed power system is characterized by widerring angolar separation of bus voltage angles as it moves towards voltage insecurity.DTs exploit the complex non-li.new relationship between voltage security status and generator varsfangutar difference in terms hierarchical roles extracted tlom a large number of off-line loadflow simulations. Several DT models were analyzed using the existing PMUS, and in the future when additional PMUS are incrementally installed. A PMU placement technique is discussed to determine the critical locations of new PMUS. The voltage security monitoring system was tested on a 360-bus subsystem inside AEP.

Electric Power Network State Tracking From Multirate Measurements

“…[19], missing SCADA measurements are extrapolated through the exponential moving average method between SCADA successive communications, and an optimization problem is solved using an extended Kalman filter. In [20], as in [21], the states of PMU unobservable buses are interpolated taking advantage of regularly updated SCADA measurements [21] or when a disturbance is detected considering recursive a priori state information [20]. Most of these approaches, however, consider that SCADA and PMU measurements are taken at one single point in time.…”

A Substation-Oriented Approach to Optimal Phasor Measurement Units Placement

“…In simple terms, (6) guarantees that every zero injection has a contribution that changes a previously unobservable bus into an observable bus, whereas (7) guarantees that, to any bus, there is no more than one neighbor zero injection (including the bus itself) contributing to its observability. The strict proof for this form of i O is provided in [32].…”

“…The techniques for solving OPP problems by using one or a combination of meta-heuristic optimization methods are developed in [5][6][7][8][9][10][11][12][13][14][15][16][17][18], and include simulated annealing, practical heuristic algorithms, genetic algorithms, particle swarm optimization, Tabu search, differential evolution, an immunity algorithm, decision trees, an iterated local search, spanning tree searches, greedy algorithms, and recursive security N algorithms. The major weakness of using intelligent search algorithms is that globally optimal solutions are not guaranteed.…”

“…Approaches based on deterministic methods as proposed in [19][20][21][22][23][24][25][26][27][28][29][30][31] attempt to build equivalent integer problems (EIP) to describe how the PMUs installed in the power system cause the whole network to be observable according to the observability rules and then solve the EIP using local or general optimization techniques. The method described in [6] was a breakthrough that used an EIP model to describe the task of PMU placement at strategic buses to make the entire system observable. The existence of constraints that consider PMU measurements, injections and flows is also discussed.…”

A short survey of methods for voltage instability detection

“…However, some recent works proposed taking advantage of PMU data [32], [33], [34], [35] and therefore are shortly presented in the next section.…”