Over the last decade, many power systems have significantly changed with the proliferation of renewable generation sources, such as wind and solar photovoltaic. Due to their variability and nonsynchronous nature, new challenges and complexities have emerged regarding operational security of modern power systems. The 2016 South Australia (SA) blackout was the first known blackout due to such a high renewable situation. An official report has recently been published to review the causes and provide the corresponding recommendations for improvement of network operation, control, and security. However, there are still a number of critical issues and debates which remain unsolved, such as network bottleneck identification, overvoltage explanation, pole slip concern, frequency dip mystery, and frequency/voltage instability debate. In this paper, based on the reconstruction of the event, these unsettled issues are prudently analyzed to unveil their root causes. In addition, an innovative scheme is proposed to prevent the blackout by identifying the network separation at an early stage. This research will not only further advance the understanding of the 2016 SA blackout, but also will provide valuable guidelines for the management of future renewable-rich networks.

There are more large-scale PV plants being established in rural areas due to availability of low priced land. However, distribution grids in such areas traditionally have feeders with low X/R ratios, which makes the independent reactive power compensation method less effective on voltage regulation. Consequently, upstream Step Voltage Regulator (SVR) may suffer from excessive tap operations with PV induced fast voltage fluctuations. Although a battery energy storage system (BESS) can successfully smooth PV generation, frequent charge/discharge will substantially affect its cost effectiveness. In this paper, a real-time method is designed to coordinate PV inverters and BESS for voltage regulation. To keep up with fast fluctuations of PV power, this method will be executed in each 5s control cycle. In addition, charging/discharging power of BESS is adaptively retuned by an active adjustment method in order to avoid BESS premature energy exhaustion in a long run. Finally, through a voltage margin control scheme, the upstream SVR and downstream PV inverters and BESS are coordinated for voltage regulation without any communication. This research is validated via an RTDS-MatLab co-simulation platform, and it will provide valuable insights and applicable strategies to both utilities and PV owners for large-scale PV farm integration into rural networks.

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. This paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. The results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.

Most traditional Var compensation-based voltage regulation methods are developed following the single-phase Volt-Var response rule. These methods typically have competent voltage regulation performance with balanced photovoltaic (PV) integration. However, certain randomness of single-phase rooftop PV installation may lead to significant PV power imbalance across three phases, especially in low voltage (LV) distribution systems. In such unbalanced situations, unintended inter-phase Volt-Var response which is ignored in the single-phase Volt-Var response rule will become significant and greatly challenge the effectiveness of the traditional methods on voltage regulation. This can further cause inverter saturation and consequently makes distribution systems vulnerable to overvoltage problems. In this paper, the mathematical equations of unbalanced three-phase Volt-Var response are first derived and analyzed to identify the strong MVE (mutual Var compensation effect) and the weak MVE. This analysis provides the theoretical foundation for the development of the proposed inter-phase coordinated consensus algorithm, which can successfully overcome PV imbalance-induced voltage regulation challenges (e.g. inverter saturation and network overvoltage), while does not need exact system parameters. The effectiveness of this method has been validated by time-series simulations with a real LV distribution system and recorded data.

This article proposes a novel algorithm employing space vector ellipse (SVE) in a complex plane to classify and visualize power quality disturbance-events (PQDEs). In the proposed method, at first, the time-domain signal and a reference signal, which are separated by 90°, are mapped in a complex 2D coordinates. Thus, the tip of resultant rotating vector traces an ellipse, from which three parameters, namely, semi-major axis, semi-minor axis and inclination angle, are obtained. Then, the ellipse parameters are exploited to classify and visualize nine types of PQDEs, namely, voltage sag, swell, interruption, harmonic, sag-harmonic, swell-harmonic, notch, flicker and transient. To validate the practicability of the proposed approach, an extensive real-time simulation study is carried out on RTDS platform using a test microgrid network to generate a large number of PQDEs. The test events were successfully classified and visualized in complex plane. Moreover, the noisy and practical signals, recorded by IEEE 1159.2 Working Group, were successfully classified to demonstrate the effectiveness of the proposed method.