Impact of prominent synchrophasor estimation algorithms on power system stability assessment

The electricity network is a critical infrastructure and its reliability is of paramount importance for the functionality of many critical systems in the modern society. Power system stability is one of the imperative aspects that impacts the reliability of electrical networks, hence power system stability needs to be observed in real-time for secure and reliable operation of the power grids. Conventionally, supervisory control and data acquisition (SCADA) based wide-area monitoring systems (WAMS) have been used for this purpose, however, they are predominantly designed to detect static changes in steady-state stability. In contrast, modern wide-area power networks pose significant challenges such as presence of power electronic switching loads and inductive motor loads, asynchronous distributed generation and dynamic fluctuations in demand and supply. Synchrophasor based WAMS is the next generation WAMS technology and offers great advantages over traditional SCADA systems such as precise time synchronisation, universally accepted standardisation and extremely fast and robust phasor estimation. A strategically placed network of phasor measurement units (PMUs) enables full visibility of the entire power network. Time synchronised PMU data can then be transferred to a phasor data centre (PDC) using efficient communication algorithms where multi facet analysis, including realtime stability assessment, could be performed. Despite significant benefits of the synchrophasor technology, several factors have hindered the widespread adoption ofthe synchrophasor technology. This research addresses such contemporary issues. The first phase of this research details an empirical study of existing synchrophasor estimation algorithms (SEAs) and considers the need for a benchmark in terms of robustness. Synchrophasor research is heavily populated with studies presenting diverse SEAs. Interestingly, not many studies have attempted to develop a robust SEA based on the mathematical technique proposed in the original Institute of Electrical and Electronics Engineers (IEEE) standardisation (i.e. IEEE std. C37.118.1-2011), the quadrature demodulation (QD) technique. Therefore, a verifiable benchmark algorithm is not currently available. This research presents comprehensive synchrophasor estimation models developed based on the QD technique and is then presented as the benchmark SEA. Proposed models are tested against all compliance requirements stipulated in the latest IEEE standardisation. Furthermore, a detailed comparison of prominent synchrophasor models is conducted against the proposed benchmark models, to understand the impact of the SEAs on the overall phasor estimation. Results establish a clear link between the accuracy/latency of the phasor estimation and the accompanying synchrophasor algorithm. The second phase of this research involves testing and comparison of synchrophasor models on hardware platforms. Even though development of SEA has been a prominent research area, only a few of these studies have been verified and validated with field tested results. This is a significant barrier to the advent of improved SEAs beyond academic literature, especially in industrial applications. A laboratory scale, hardware based synchrophasor test platform is proposed where any synchrophasor algorithm can be tested for any test condition or fault signal. Key highlights of this section include; global position system (GPS) time synchronisation of synchrophasors and a sinusoidal pulse width modulation (SPWM) technique based scalable input system capable of generating measurement conditions emulating any fault condition. Results establish the superiority of the proposed benchmark algorithm and identify key implementation issues in hardware implementation of some of the prominent synchrophasor models. The final phase of this research develops a synchrophasor based WAMS by using a bottom-up approach to evaluate real-time stability of wide-area networks under practical power network fault conditions. As part of this research the analyses and the impact of SEAs on the overall stability assessment has been evaluated. Development and testing of PMUs, and stability studies are historically conducted in two disjointed silos. As a result, stability analysis is often conducted based on the assumption that the PMU data delivered to the PDC are accurate and instantaneous. On the other hand, SEAs are tested against the compliance criteria listed in the IEEE standardisation which do not involve any practical power network faults. This study attempts to dive into this unexplored territory. Performance in realtime voltage and frequency stability of prominent SEAs is evaluated by employing a strategically placed PMU network on two standard power networks simulation models. The IEEE 9-bus system and New England 39-bus system are considered and consists synchronous generation sources, dynamic load centres and transmission links. By modelling practical transient fault conditions such as short circuit faults, loss of generation and addition of load centres, the real-time voltage and frequency stability have been studied. A modified highest Lyapunov exponent (HLE) based real-time stability assessment algorithm (RSAA) is proposed to suit implementation in practical power networks. Despite the full compliance against the IEEE standardisation, tested algorithms produce significantly different outcomes in the stability assessment that may directly impact on the subsequent activation of protection systems and overall network stability. Results of this study point to interesting findings and establishes a clear link between the reliability and the performance of the underlining SEA. In conclusion, key findings of this research contribute to two prominent areas within the synchrophasor research; SEA development and testing, and real-time stability assessment. This research has established a strong link between these disjointed research fields, thereby enabling future advancements synchrophasor based stability monitoring and control systems