Abstract-Voltage collapse is a critical problem that impacts power system operational security. Timely and accurate assessment of voltage security is necessary to detect post-contingency voltage problems in order to prevent a large scale blackout. This paper presents an online voltage security assessment scheme using synchronized phasor measurements and periodically updated decision trees (DTs). The DTs are first trained offline using detailed voltage security analysis conducted using the past representative and forecasted 24-h ahead operating conditions. The DTs are also updated every hour by including newly predicted system conditions for robustness improvement. The associated synchronized critical attributes are obtained in real time from phasor measurement units (PMUs) and compared with the offline thresholds determined by the DTs to assess security. This approach is tested on the American Electric Power (AEP) system and properly trained DTs perform well in assessing voltage security. Several new ideas to improve DT performance are also introduced. Index Terms-Decision trees, online security assessment, phasor measurement units, voltage collapse. Voltage phase angle of node x minus that of y. Critical splitting rule in the decision tree. Decision tree. Current flow on branch between nodes x and y. Learning set. Other bus. Operating condition. MVAr flow on branch between nodes x and y. Test set. Square of the measured voltage magnitude. Current magnitude multiplied by branch impedance between nodes x and y. II. INTRODUCTION ODERN power systems are interconnected by transmission lines for both reliability and economic reasons. Countries with highly developed economies have seen the consumption of electric power rise at consistent annual rates, but more recently the load growth has not resulted in a concomitant increase in the transmission capability due to the difficulty of siting and approving new transmission lines [1] . Hence, power networks are likely to be operated under greater stress with transmission lines carrying electric power near their limits during peak load periods. In such situations, the loss of critical transmission lines or transformers may cause a continuous decline of bus voltages and result in a voltage collapse if the system lacks effective reactive power support [2] . Voltage collapse is one of the most critical problems that threaten system secure operations. It is usually initiated by: 1) a continuous load increase, and/or 2) a major change in network topology resulting from a critical contingency. During a voltage collapse event, bus voltages in a localized area decrease below an acceptable level. Without timely control actions, the low voltages may spread throughout adjacent areas of the power system and may eventually cause a large scale blackout instead of a localized outage. The time span for voltage instability ranges from 0.1 s to 1 h, representing transient and long-term voltage instability, respectively [2], [3] . For the fast transients, detailed voltage security analysis for online applications is a great challenge because of the high computational burden. As a result, an accurate assessment tool to determine the voltage security in real time becomes a necessity for system operators to determine remedial controls for preventing voltage collapse. This paper focuses on the voltage collapse problems caused by severe disturbances in the system and presents a three-step decision tree-based scheme for online voltage security assessment using phasor measurements. The main procedures include: 1) conducting detailed post-contingency voltage security analysis for the past and predicted operating conditions (OCs) and training DTs offline from created databases containing these analysis results; 2) periodically updating the DTs by including anticipated OCs for the next hour to reduce the likelihood of misclassifications on whether the system is secure or insecure; and 3) continuously collecting the corresponding PMU measurements selected as critical attributes in the DTs. 0885-8950/$25.00
Specifically, Diao et al. develop and train a decision tree using PMU data to assess voltage security REF ).
Decision Tree-Based Online Voltage Security Assessment Using PMU Measurements
IEEE Transactions on Power Systems
IEEE Transactions on Power Systems
Engineering