Swakshar Ray

A New Approach to Continuous Latency Compensation With Adaptive Phasor Power Oscillation Damping Controller (POD)

Latency or delay in remote feedback signals can adversely affect the closed-loop damping performance. Accurate time-stamp information at both (PMU location and control center) ends offers a possibility to continuously compensate for time-varying latency. In this paper, an adaptive phasor power oscillation damping controller (APPOD) is proposed wherein the rotating coordinates for phasor extraction are adjusted to account for the change in phase caused due to the delay. The oscillatory component of the original signal is thus retrieved out of the delayed signal received at the control center. Unlike conventional phasor POD, which uses a fixed phase shift to generate damping control signal, an adaptive phase shift algorithm is used here to suit varying signal locations and operating conditions. Case studies confirm the effectiveness of the proposed technique, both in terms of robustness and handling continuously varying delays. A comparison with a conventional gain scheduled POD (CGPOD) and a Unified Smith Predictor (USP) approach is also presented.

Appropriate signal selection for damping multi-modal oscillations using low order controllers

This paper highlights the importance of considering the phase angle of the residues (residue angle) in addition to their magnitude while selecting appropriate feedback signals for damping control design. Residue angle is closely related to the phase compensation requirement at each modal frequency and hence should not differ significantly over adjacent frequencies. This is especially true when the required phase compensation has to be provided by a limited number of lead-lag blocks which cannot change the phase appreciably over a narrow frequency range. Moreover, the signals should be selected such that the residue angles do not vary much over different operating conditions. Use of such phase angle criterion results in a set of signals which yield better performance compared to signals selected based only on the magnitude of residues. This is illustrated through simulation on a test system.

Power oscillation damping control using wide-area signals: A case study on Nordic equivalent system

Power oscillation damping (POD) control employing wide-area signals is illustrated in an equivalent system model representing key characteristics of Nordic power system. Phasor measurement units (PMUs) in Norway and Finland are used to obtain feedback signals for supplementary control of a large SVC unit located in the south-east of Norway. Comparison has been made between two control design approaches- (i) robust linear time invariant model based POD (MBPOD) - dependant on accurate system model and (ii) indirect adaptive POD (IAPOD) - which is fixed structure but time-varying and relies only on measurements. An optimization problem is formulated to design the controller parameters for MBPOD while the IAPOD is based on online Kalman filter estimation and adaptive pole-shifting control. Performances of both MBPOD and IAPOD are found to be quite similar even though IAPOD requires very little prior information about the system. A number of simulations are carried out under different tie-line outages to verify the performance.

Multivariable Self-Tuning Feedback Linearization Controller for Power Oscillation Damping

The objective of this brief is to design a measurement-based self-tuning controller, which does not rely on accurate models and deals with nonlinearities in system response. A special form of neural network (NN) model called feedback linearizable NN (FLNN) compatible with feedback linearization technique is proposed for representation of nonlinear power systems behavior. Levenberg-Marquardt (LM) is applied in batch mode to improve the model estimation. A time-varying feedback linearization controller (FBLC) is employed in conjunction with the FLNN-LM estimator to generate the control signal. Validation of the performance of proposed algorithm is done through the modeling and simulating both normal and heavy loading of transmission lines, when the nonlinearities are pronounced. Case studies on a large-scale 16-machine five-area power system are reported for different power flow scenarios, to prove the superiority of proposed scheme against a conventional model-based controller. A coefficient vector Λ for FBLC is derived and used online at each time instant, to enhance the damping performance of controller.

A wide area measurement based neurocontrol for generation excitation systems

Power system is a highly interconnected nonlinear system that needs optimal and accurate control for continuous operation. Large power transfer through long transmission line between different electrical areas, stressed system and adverse interaction between local controllers, may give rise to slow frequency inter-area oscillations. The inter-area modes may not be visible from local measurements and hence it is useful to use remote measurement based centralized supplementary control. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control to local controllers such as automatic voltage regulators, power system stabilizers, etc. to damp out inter-area oscillations. This paper presents a design and real time implementation of a nonlinear neural network based optimal wide area controller using adaptive critic design (ACD). The real time implementation of a power system model is carried out on a real time digital simulator (RTDS). The performance of the WACS as a power system stability agent is studied using a two-area power system under different operating conditions and contingencies. The WACS shows improvement in the damping of inter-area mode with the use of supplementary excitation control. In addition, results show that the designed controller can provide robust performance under small communication delay in remote signal transmission.

Online Levenberg-Marquardt algorithm for neural network based estimation and control of power systems

Levenberg-Marquardt (LM) algorithm, a powerful off-line batch training method for neural networks, is adapted here for online estimation of power system dynamic behavior. A special form of neural network compatible with the feedback linearization framework is used to enable non-linear self-tuning control. Use of LM is shown to yield better closed-loop performance compared to conventional recursive least square (RLS) approach. For successive disturbance use of LM in conjunction with non-linear neural network structure yields faster convergence compared to RLS. A case study on a test system demonstrates the effectiveness of the online LM method for both linear and nonlinear estimation over RLS estimation (linear).

A case study on challenges for robust wide-area phasor POD

This paper illustrates the challenges towards achieving a robust phasor POD (power oscillation damping), a concept introduced and developed by ABB. A Phasor POD extracts the oscillatory part of the measured signal in the form of a phasor and applies a suitable phase shift to derive the damping control action. For a thyristor controlled series capacitor (TCSC), a phase shift of 90 degrees with respect to local power flow is recommended. However, the present case study on a simple test system with a TCSC reveals that a 90 degree phase shift on the local power does not necessarily yield the desired results. In fact, the phase shift required for satisfactory performance differs from one operating condition to another. Use of a wide-area signal (wide-area phasor POD) is shown to improve the damping functionality compared to local power flow provided an appropriate phase shift — which might not be intuitive — is given. Moreover, extraction of individual phasors out of a multi-modal signal is a challenge for practical systems exhibiting complex multi-modal behavior.

Self-tuning feedback linearization controller for power oscillation damping

Power systems exhibit highly nonlinear behavior especially under large disturbances like faults, outages etc. necessitating application of nonlinear control techniques. Nonlinear estimation and control of power oscillations through FACTS devices is illustrated in this paper. A special form of nonlinear neural network compatible with the feedback linearization framework is used. Levenberg-Marquardt (LM) algorithm is adapted to work in sliding window batch mode for online estimation of system oscillatory behavior. At each sampling interval the estimated neural network parameters are used to derive appropriate control using the feedback linearization technique. Use of LM is shown to yield better closed-loop performance compared to conventional recursive least square (RLS) approach. A case study is presented to demonstrate the effectiveness of feedback linearization controller (FBLC), especially, under stressed operating conditions. Its performance is compared against pole-shifting controller (PSC) under different scenarios.

A new approach to continuous latency compensation with adaptive phasor power oscillation damping controller (POD)

Latency or delay in remote feedback signals can adversely affect the closed-loop damping performance. Accurate time-stamp information at both (PMU location and control center) ends offers a possibility to continuously compensate for time-varying latency. In this paper, an adaptive phasor power oscillation damping controller (APPOD) is proposed wherein the rotating coordinates for phasor extraction are adjusted to account for the change in phase caused due to the delay. The oscillatory component of the original signal is thus retrieved out of the delayed signal received at the control center. Unlike conventional phasor POD, which uses a fixed phase shift to generate damping control signal, an adaptive phase shift algorithm is used here to suit varying signal locations and operating conditions. Case studies confirm the effectiveness of the proposed technique, both in terms of robustness and handling continuously varying delays. A comparison with a conventional gain scheduled POD (CGPOD) and a Unified Smith Predictor (USP) approach is also presented.

Interaction between conventional and adaptive phasor power oscillation damping controllers

Adaptive phasor power oscillation damping controllers (APPODs) produce superior large signal performance with very little reliance on accurate system models. However, recursive phasor estimation, online frequency correction and adaptive phase-shift are involved which makes modeling such APPODs difficult in stability studies. Possible interaction with other controllers (e.g. lead-lag compensators) is thus unforeseeable restricting their acceptability in practice. In this paper potential interaction between an APPOD and a conventional POD (CPOD) is investigated. The study is primarily simulation based as mathematical analysis of such interaction is not straightforward due to highly complex non-linear nature of APPODs. Simulation results presented here show no adverse interaction which needs to be substantiated for large-scale systems.