Power System Stabilizer Tuning Based on Multiobjective Design Using Hierarchical and Parallel Micro Genetic Algorithm

In order to achieve the optimal design based on some specific criteria by applying conventional techniques, sequence of design, selected locations of PSSs are critical involved factors. This paper presents a method to simultaneously tune PSSs in multimachine power system using hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) based on multiobjective function comprising the damping ratio, damping factor and number of PSSs. First, the problem of selecting proper PSS parameters is converted to a simple multiobjective optimization problem. Then, the problem is solved by a parallel micro GA based on HGA. The stabilizers are tuned to simultaneously shift the lightly damped and undamped oscillation modes to a specific stable zone in the s-plane and to self identify the appropriate choice of PSS locations by using eigenvalue-based multiobjective function. Many scenarios with different operating conditions have been included in the process of simultaneous tuning so as to guarantee the robustness and their performance. A 68-bus and 16-generator power system has been employed to validate the effectiveness of the proposed tuning method

New heuristic-based design of robust power system stabilizers

This paper proposes a new robust design of power system stabilizers (PSSs) in a multimachine power system using a heuristic optimization method. The structure of each PSS used is similar to that of a conventional lead/lag stabilizer. The proposed design regards a multimachine power system with PSSs as a multi-input multi-output (MIMO) control system. Additionally, a multiplicative uncertainty model is taken into account in the power system representation. Accordingly, the robust stability margin can be guaranteed by a multiplicative stability margin (MSM). The presented method utilizes the MSM as the design specification for robust stability. To acquire the control parameters of PSSs, a control design in MIMO system is formulated as an optimization problem. In the selection of objective function, not only disturbance attenuation performance but also robust stability indices are considered. Subsequently, the hybrid tabu search and evolutionary programming (hybrid TS/EP) is employed to search for the optimal parameters. The significant effects of designed PSSs are investigated under several system operating conditions

Forced oscillation detection amid communication uncertainties

This article proposes a novel technique for the detection of forced oscillation (FO) in a power system with the uncertainty in the measured signals. The impacts of communication uncertainties on measured signals are theoretically investigated based on the mathematical models developed in this article. A data recovery method is proposed and applied to reconstruct the signal under the effects of communication losses. The proposed FO detection with communication uncertainties is evaluated in the modified 14-machine Southeast Australian power system. A rigorous comparative analysis is made to validate the effectiveness of the proposed data recovery and FO detection methods

A Stabilization of Frequency Oscillations in a Parallel AC-DC Interconnected Power System via an HVDC Link

This paper presents a new application of High Voltage Direct Current (HVDC) link to stabilization of frequency oscillations in a parallel AC-DC interconnected power system. When an interconnected AC power system is subjected to a large load with rapid change, system frequency may be considerably disturbed and becomes oscillatory. By utilizing the system interconnections as the control channels of HVDC link, the tie-line power modulation of HVDC link through interconnections is applicable for stabilizing the frequency oscillations of AC systems. In the design of power modulation controller, the technique of overlapping decompositions and the eigenvalue assignment are applied to establish the state feedback control scheme. To evaluate control effects, a linearized model of a parallel AC-DC interconnected system, including a power modulation controller of HVDC link, is investigated by simulation study. Simulation results show that the proposed controller is not only effective in damping out frequency oscillations, but also capable of alleviating the transient frequency swing caused by a large load disturbance

Control of distributed converter-based resources in a zero-inertia microgrid using robust deep learning neural network

Considering the evolution of future microgrids (MGs) towards zero-inertia level due to the penetrations of distributed converter-based resources (DCRs), a large number of data produced by these generations will lead the control decisions to be more complicated than conventional power systems. This paper presents a control strategy for a zero-inertia MG with DCRs using a robust deep learning neural network (RDeNN). In a training phase, a sub-space state-based identification method is employed to monitor and analyze the data regarding stability indices, i.e., damping and frequency of dominant modes, and robustness against uncertainties. In addition, a mixed H2/