This chapter presents the real-time laboratory implementation/testing of smart wide-area monitoring system (smart-WAMS) algorithm. The smart-WAMS is the published approach to monitor power oscillations by the first two authors of this chapter. Smart-WAMS consumes the phasor measurement unit (PMU) signal and gives the accurate real-time information about the critical modes present in the system. However, in this chapter, the smart-WAMS is restructured to track the well-experienced critical mode in real time. The testing is done in national smart grid laboratory (NSGL), SINTEF, Norway under "ERIGrid transnational access" project awarded by European Union-Horizon 2020. The three power system networks are considered for testing and the first one is the "Nordic grid" system, the second is the offline "IEEE-39 bus system," and the last is the "North American SynchroPhasor Initiative (NASPI)" system. The real-time tracking of power oscillations is shown in video results.

This article illustrates the laboratory based real-time testing of smart wide-area monitoring systems (smart-W AMS). The smart-WAMS approach has already been published by the authors of this paper and it has been proven very effective in wide-area monitoring of power oscillations. Smart-WAmsconsumes the phasor measurement unit (PMU) signal and gives the accurate real-time information about the various critical modes present in the system. The dominant low frequency modes can be tracked in real-time in terms of its frequency and amplitude deviation. The testing is done using real-time simulator, Opal-RT. The two power system networks are considered for testing. The first one is the offline IEEE 39 bus system which is simulated in real-time environment in Opal-RT and the second one is the online Nordic grid system. The procedure and the relevant details involved in the testing are explained and the obtained results are also discussed.

This article presents internal model control (IMC) based decentralized reinforce-control of renewable dynamic virtual power plant (DVPP) so that, it can be integrated into the power system as a substitution of fuel-based conventional generators. Such grid integration towards net-zero targets could not be possible without providing additional ancillary service (AS) to the power system, as the traditional AS would fall short with the retirement/substitution of conventional generators. The theory of DVPP from a technical perspective (i.e., TDVPP) is presented in a detailed and simplified manner, including the formulation of a generalized control objective (desired specification) for DVPP integration. The solution approach includes two steps: (1) disaggregation of desired specification and (2) decentralized reinforce-control to match the disaggregated specification. The theory and solution approach for DVPP integration is presented in a generalized manner enabling the DVPP to offer multiple ASs, but the case study is limited only to frequency control AS (FCAS) in this article. The study is performed on the 'western system coordinating council (WSCC)' test system, in which an attempt is made towards net-zero targets by substituting the largest thermal generator with renewable DVPP ensuring the grid's operation or dynamics safe.

This article presents a study on real-time testing of synchrophasor-based "wide-area monitoring system's applications (WAMS application)." Considering the growing demand of real-time testing of "wide-area monitoring, protection, and control (WAMPAC)" applications, a systematic real-time testing methodology is formulated and delineated in diagrams. The diagrams propose several stages through which an application needs to be assessed (sequentially) for its acceptance prior to implementation into a production system. However, only one stage is demonstrated in this article which comprises the use of a prototyping software toolchain and whose potential is assessed as sufficient for preliminary real-time testing (PRTT) of WAMS applications. The software toolchain is composed of two components: the MATLAB software for application prototyping and other open-source software that allows ingesting prerecorded phasor measurement unit (PMU) signals. With this software toolchain, a PRTT study is presented for two WAMS applications: "testing of the PMU/phasor data concentrator (PDC)" and "testing of wide-area forced oscillation (FO) monitoring application."

This article develops and demonstrates the software toolchain for real-time testing of synchrophasor based algorithms. Real-time testing procedure being the need of smart grid, requires to be hassle-free and easily accessible to the researchers. The developed software toolchain combines both MATLAB and open-source software. The toolchain requires recorded phasor measurement unit (PMU) or phasor data concentrator (PDC) signals, which are then played-back in real-time in the same computer using local sockets. The data is replayed using transmission control protocol/internet protocol (TCP/IP) sockets and the IEEE C37.111-2013 data transfer standard. The data is then retrieved and processed in real-time by any synchrophasor based algorithm in MATLAB. The toolchain is demonstrated with two examples, one that shows the main functionality by testing the connection with a PMU/PDC and another testing of a wide-area forced oscillation (FO) monitoring algorithm.

This paper presents the study related to the power system stabilizer (PSS) design for northern regional power grid (NRPG) of India. The location of local PSS is suggested by participation factor approach. The power-voltage reference (PVr) characteristic of the suggested generator is used to obtain the compensator block of the local PSS. Internal states are lost while performing model order reduction therefore, the shaft dynamics are not available in the reduced order model for disabling. Therefore compensating block has to be design by utilizing full order system. But, the gain of the PSS can be tuned by utilizing the reduced order model. Next, the model order reduction (MOR) is performed with a target on preserving the characteristics and behavior of dominant inter-area mode in reduced order model (ROM). Thereafter, the tuned gain using ROM is combined with compensator and washout filter to obtain PSS for 44th generator (G44). The performance of designed PSS is investigated under five cases of disturbances.

This paper studies the model order reduction (MOR) of large scale system i.e. Northern Regional Power Grid (NRPG) system of India so that the design of damping control becomes less complex. The linearized NRPG system is obtained in power system toolbox (PST) to carry out the MOR study. The eigenvalue analysis is conducted for a full order system to obtain the characteristics and behavior of inter-area modes and the controller location is also identified for dominant inter-area mode. The MOR is done with a target on preserving the characteristics and behavior of dominant inter-area mode in reduced order model (ROM). For verifying the same characteristics and behavior of desired mode in ROM, four aspects are considered which are, mode characteristics, modal observability, model controllability, and step response. The recently upgraded application of MATLAB called "model reducer" app is utilized to reduce the full order system of NRPG.

This article presents a modified least-square (MLS) method for model order reduction (MOR) of the higher order continuous-time systems by matching the time moments and Markov parameters. The MLS method is based on the selection of number of time moments and Markov parameters which are to be matched that could preserve the characteristics of high order model (HOM) into the reduced-order model (ROM). The key contribution of this article is the formulation of modified matrix expression to obtain the coefficients of numerator and denominator of ROM. It is shown that a combination of time moments and Markov parameters is required to be matched in order to preserve the transient and steady-state responses. The effectiveness of the proposed approach is shown by numerical examples.

This article gives a new method to identify the frequency of Forced Oscillation (FO) in phasor measurement units (PMUs) signals. The processing of the signal by Empirical Mode Decomposition (EMD) technique leads to effective detection with improvement in accuracy. After testing some improved versions of EMD, it is observed that 'improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN-2014)' is the best version to use in processing. The developed methodology is able to spot the frequency of FOs even if there exist multiple modes with mode mixing and multiple events. In such cases, self-coherence method fails to spot FO. Spectral analysis is conducted on the decomposed Intrinsic Mode Functions (IMFs) in order to determine the frequency of FO. The analysis with proposed methodology is done on simulated signal as well as on real-time PMUs signal taken from North American SynchroPhasor Initiative (NASPI).

This study presents a systematic approach to monitor sustained oscillations in real-time power systems. In general, monitoring of sustained oscillation means detection of oscillating frequency, its time range, type, and source of sustained oscillation. The basic steps adopted in paper include double-stage mode decomposition (DSMD), spectral and statistical analysis. The DSMD follows decomposition of signals by using improved complete ensemble empirical mode decomposition with adaptive noise followed by further decomposition by using variational mode decomposition to obtain rich dominant mode. It is shown that decomposed mode obtained by DSMD carries monotonic frequency component. The proposed approach is validated on simulated signals and real-time phasor measurement unit signals. The frequency and time duration of interarea and forced oscillations are distinctly detected. Also, the source of forced oscillations is identified in study. The proposed approach is more effective and accurate in wide-area monitoring than the other spectral-based methods for oscillation analysis in phasor measurement unit signals.

This study presents a dynamic approach for determining mode shape using time-domain signal. Signal processing techniques, mode decomposition, and spectral analysis are used here. The quality of signal affects the performance of spectral analysis, especially for estimation of low-frequency modes. Therefore, before applying spectral analysis, low-frequency modes are extracted using mode decomposition technique, so that the decomposed modes (DMs) may indicate centre frequency in its spectrum. In the study, two-stage mode decomposition approach is proposed for accurate and effective mode decomposition. The power spectral density (PSD) and cross-PSD tools are used to process DMs for estimation of mode frequency and determination of mode shape, respectively. The proposed dynamic approach is tested on simulated signals of IEEE 16-machine 68-bus test system and real-time phasor measurement units (PMUs) signal. The results obtained using proposed dynamic approach on simulated signals are compared with those obtained by steady-state approach, i.e. eigenvalue analysis.

This paper presents spectral-based dynamic approach for mode shape estimation by using time-domain signals. The approach in this paper is applied on software simulated signals which partially resembles the PMU signals. Power System Toolbox (PST) is used to simulate IEEE 16 machine 68 bus test system to generate multiple signals. Empirical mode decomposition (EMD) decompose multimode signal into separate modes but perfect decomposition by EMD is not always guaranteed therefore two mode decomposition techniques are used at two stages for effective mode decomposition. Power Spectral Density (PSD) and Cross Power Spectral Density (CPSD) tools are used to process decomposed modes for estimation of mode frequency and mode shape respectively. The mode shape results are compared and verified with the conventional approach i.e., eigenvalue analysis. Comparison shows that the approach is effective in mode shape estimation and hence it could also be applied on real-time PMU signals.

This paper presents the study on local PSS control for Northern Regional Power Grid (NRPG) system of India. The complete analysis is conducted in MATLAB®. Power System Toolbox (PST) is used to obtain the linearized state space model of NRPG. Eigenvalue analysis suggests one poorly damped inter-area mode. The locations for two local Power System Stabilizers (PSSs) are suggested by modified residue approach. The PVr characteristics of the generators are used to design the compensating blocks of local PSSs which is the key step in PSSs design. For large scale power systems, MATLAB is used first time for designing the compensating blocks of PSSs by using its latest app, “control system designer”.

This paper presents a systematic approach to detect the frequency of Forced Oscillation (FO) in real-time signals obtained from phasor measurement units (PMUs). It is shown that, preprocessing of the signal by Empirical Mode Decomposition (EMD) technique leads to effective detection. The designed methodology can detect the frequency of FOs even in the presence of multiple mode mixing, whereas the self-coherence method fails to detect. Spectral analysis is performed on the Intrinsic Mode Functions (IMFs) to determine the frequency of FO. To further confirm the sustainability of the oscillation, spectral analysis of time-delayed signals is also performed and the results are discussed. The study is investigated on both simulated signal and real-time PMU signal of North American SynchroPhasor Initiative (NASPI). Two forced oscillations; FO 1 (14.67 Hz) and FO 2 (4.62 Hz) are detected in the NASPI PMU's signal by the proposed approach.

This paper presented results on 'small signal stability' and 'coherency' analysis of Northern Regional Power Grid (NRPG) system of India. Analysis is conducted by using modelling data of NRPG in Power System Toolbox (PST). The study based on modelling data of NRPG system is presented first time in this article. Conventional approaches, “eigenvalue analysis” and “slow & tight coherency analysis” are used for 'small signal stability' and 'coherency' analysis respectively. Mode shape of inter-area mode, local mode and participation factors for inter-area mode are shown. 'Slow coherency' method gives nine coherent areas by using nine slowest modes whereas 'tight coherency' method gives sixteen coherent areas for the same number of slowest modes.