Guest Editorial: New Trends in Wide‐Area Monitoring and Control of Power Systems with Large Scale Renewables (2017)

The increasing penetration of distributed and/or aggregated renewables, and the wide utilization of power electronic devices, have brought unprecedented challenges into modern power systems such as, the weakly damped oscillation caused by wind farms connected through long distance transmission lines, the frequency stability problem induced by the reduction of inertia, and the voltage stability issue resulted from the interactions between FACTS and dynamic loads. On the other hand, recent decades have witnessed the fast development of synchronised phasor measurement technologies, with more and more PMUs and WAMSs deployed all over the world. PMU/WAMS based technologies can be generally applied to the broad fields of power system online monitoring, dynamic stability assessment, and real-time control and protection. Such advanced tools and platforms provide immense opportunities to gain in-depth insights into the system dynamics and tackle the above challenges facing today's power systems. The objective of this Special Issue is to address the emerging concepts, methodologies, and applications of wide-area monitoring, control, and protection in the era of smart grids. The accepted 19 papers in this issue fall into three categories, which are briefly summarised in the following. The paper Dynamic synchrophasor estimation by Taylor-Prony method in harmonic and non-harmonic conditions by Khodaparast et al. describes a phasor estimation approach by combining the least square based Prony analysis with Taylor expansion. With the capability in handling both harmonic and non-harmonic conditions, it can accurately estimate dynamic phasors during power swings. In the paper Inter-harmonics monitoring method based on PMUs, Liu et al. develop an inter-harmonics monitoring method based on complex number synchrophasor measurements. This method manages to efficiently measure the inter-harmonics during subsynchronous oscillation events induced by the integration of large-scale renewables. In the paper Determination of mode shapes in PMU signals using two stage mode decomposition and spectral analysis, Kumar et al. propose a comprehensive approach to low-frequency oscillation mode monitoring. In this work, a two-stage mode decomposition method is combined with power spectral analysis, resulting in accurate estimation of mode frequencies and determination of mode shapes. Chen et al. present a method for generator damping estimation using ambient data during normal operation of power systems in their paper Online monitoring of generator damping using dissipation energy flow computed from ambient data. By computing the dissipation energy flow into a generator with ambient phasor measurements, the generator damping is estimated by the rate of change of the dissipation energy flow, which also represents the rate of transient energy dissipation of the generator. The paper Disturbance location determination based on electromechanical wave propagation in FNET/GridEye: a distribution-level wide-area measurement system by You et al. introduces a method to locate power system disturbances using wide-area synchropahsor measurements. With the visualised platform FNET/GridEye, this method is able to accurately pinpoint the disturbance location based on electromechanical wave propagation. In the paper Wide-area coherency identification of generators in interconnected power systems with renewables by Lin et al., a generator coherency identification approach is developed for interconnected power systems with aggregated renewable sources. The identification is carried out using an agglomerative hierarchical clustering algorithm that clusters generators with multiple trajectory similarity indices. Focusing on the same topic, Na et al. fulfill the task of coherency identification based on smoothed pseudo-Wigner-Ville distribution signal processing in their paper Identification of coherency and critical generators set in real-time signal. In addition, they develop an energy function based Lagrangian method to detect the critical generators that go out of step after faults. This method is expected to further provide system operators with direct information for generator dispatch. In the paper Optimal PMU placement considering state estimation uncertainty and voltage controllability by Zhang et al., considering both zonal voltage controllability and voltage magnitude estimation in cooperation with SCADA, the authors investigate the optimal PMU placement scheme. In particular, they formulate the optimisation problem as a multi-objective minimal Ncut partitioning problem, and utilise spectral clustering to efficiently figure out the optimal clustering boundaries that indicate the resulting optimal placement layout. The paper Successful deployment and operational experience of using linear state estimator in wide-area monitoring and situational awareness projects by Zhang et al. presents successful pilot projects of deploying the PMU based linear state estimator (LSE) technology at multiple utilities in the USA. It shows that the LSE has been enhanced to an industrial grade for real-time operation and control. Besides, it summarises the benefits and use cases from utilities’ firsthand implementation and deployment experience, which are valuable to the industry. In the paper Robust classification model for PMU-based on-line power system DSA with missing data, taking the unavailability of PMU measurements during unintentional events into consideration, Zhang et al. develop a robust classification model using machine learning techniques for dynamic security assessment. After identifying the observability of different PMU combinations in the system, they train an ensemble of random vector functional link networks with observability-constrained feature subsets. The ensemble model can support accurate dynamic security assessment under both normal and abnormal data collection conditions. Similar to the above work of data-driven dynamic security assessment, in the paper Wordbook-based light-duty time series learning machine for short-term voltage stability assessment, Zhu et al. propose a symbolic time series based learning machine to perform online short-term voltage stability assessment. This learning machine converts numerical time series into compact symbolic words, and introduces a new concept called wordbook learning to implement online stability assessment. Due to its lightness and capability in data representation, the learning machine manages to maintain both high efficiency and accuracy. In the paper Dynamic impact analysis of DFIG-based wind turbine generators on low-frequency oscillations in power system, Gupta et al. investigate the impacts of doubly fed induction generators (DFIGs) on system damping. After finding that the impacts may be either negative or positive, which are related to the locations of DFIGs, they attempt to suppress negative impacts by optimally tuning power oscillation dampers with input signals acquired from PMUs so as to improve system small signal stability. In the paper Adaptive wide-area power oscillation damper design for photovoltaic plant considering delay compensation, based on heuristic dynamic programming, Shen et al. design an adaptive damping controller for photovoltaic plants to help damp the inter-area oscillation mode. Besides its model-free nature, the controller compensates wide-area communication delays via an adaptive delay compensator. In the paper Two-level coordinated controllers for robust inter-area oscillation damping considering impact of local latency by Surinkaew et al., a centralised- and local-level coordinated control scheme using power oscillation dampers and power system stabilisers is developed to damp power oscillations. In the scheme, the centralised-level controllers act as the primary dampers, and the local ones serve as backup dampers when communication failure occurs. Controllers’ parameters are optimised based on the worst scenarios determined by the lowest damping ratio, so as to achieve the overall robustness for the scheme. The paper Adaptive nonlinear neural control of wide-area power systems by Meng et al. proposes a neural network based excitation control strategy for wide-area power systems. It utilises a two-level neural network to approximate system dynamics in an online manner, and its design procedure does not need parameter tuning, which is likely to make it more robust. In addition, the stability of the closed-loop control system is ensured via Lyapunov function analysis. The next paper Dynamic performance improvement of New York State Power Grid with multi-functional multi-band power system stabilisers based wide-area control by Rimorov et al. describes a wide-area control scheme based on multi-functional multi-band power system stabilisers in New York State Grid. Taking oscillation damping and closed-loop frequency and voltage control into comprehensive account, the scheme not only achieves oscillation damping, but also helps enhance long-term voltage stability. The paper Decentralised coordinated secondary voltage control of multi-area power grids using model predictive control by Morattab et al. presents a decentralised control scheme for coordinated secondary voltage control in large-scale power networks. Based on model predictive control, it takes measured reactive power deviation on the tie-liens between neighboring areas as the measured disturbance and strives to balance it in real time. With this merit, the control scheme gains adaptability to load variations and communication delays. Perron et al. introduce a robust voltage control system to control various dynamic shunt compensators on the Hydro-Québec network in their paper Wide-area voltage control system of flexible AC transmission system devices to prevent voltage collapse. The control system measures voltage variations in the load area and adjusts the operation set point of each shunt compensator accordingly, thus avoiding voltage collapse resulting from extreme contingencies. Gou et al. develop a real-time transient stability analysis and emergency control scheme based on a pair-wise relative energy function in their paper Novel pair-wise relative energy function for transient stability analysis and real-time emergency control. The scheme computes the capacity of the requisite generation curtailment via the pre-calculated relative energy of the equivalent post-fault system. The appropriate location for implementing emergency control is further determined by tracking relative energy oscillation trajectories. Tremendous efforts have been devoted to wide-area power system monitoring and control with large scale renewables integrated in recent years. With the above state-of-the-art research papers, this Special Issue tries to provide an overview of the emerging advances and trends in this area. Although significant progress has been made by far, there still exist great potentials beneath PMUs/WAMSs, especially the valuable information underlying massive high-resolution PMU data, which could be fully leveraged to better monitor and control the future power networks. We hope this Special Issue can inspire more innovative PMU/WAMS based researches, technologies, and applications in the power engineering community. Chao Lu received his B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 1999 and 2005, respectively. He is currently an Associate Professor with the Department of Electrical Engineering, Tsinghua University. His research interests include power system analysis and control, and intelligent control applications. Tianshu Bi received her Ph.D. degree from the Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong, in 2002. She is currently a Professor at North China Electric Power University, Beijing, China. Her research interests include power system protection and control, synchronised phasor measurement technique, and its application. Marija Ilic is currently a Professor with Carnegie Mellon University, Pittsburgh, PA, USA, with a joint appointment in the Electrical and Computer Engineering and Engineering and Public Policy Departments. She is also the Honorary Chaired Professor for the Control of Future Electricity Network Operations, Delft University of Technology, Delft, The Netherlands. She has 30 years of experience in teaching and research in the area of electrical power system modeling and control. Her current research interests include systems aspects of operations, planning, and economics of the electric power industry. She has co-authored several books in the above areas. She is an IEEE Distinguished Lecturer. Kevin Tomsovic received his B.Sc. degree from Michigan Technological University, Houghton, MI, USA, in 1982, his M.Sc. and Ph.D. degrees from the University of Washington, Seattle, WA, USA, in 1984 and 1987, respectively, all in electrical engineering. He is currently the CTI Professor with the Department of Electrical Engineering and Computer Science (EECS), The University of Tennessee, Knoxville, TN, USA, where he also directs the NSF/DOE Engineering Research Center CURENT. Xiaoyu Wang is an Associate Professor of the Department of Electronics at Carleton University, Ottawa, Canada. Since 2016 he has served as a Board Member of the IEEE Canada Conference Editorial Board. He is also the Chair of the IEEE Power and Energy Society (PES) Task Force on Interfacing Techniques for Simulation Tools. He is a recipient of the Ontario Early Researcher Award in 2017.