Interarea Power System Oscillations Damping via AI-based Referential Integrity Variable-Structure Control

Power system oscillation is an unavoidable threat to the stability of an interconnected modern power system. The reliable operation of a modern power system is widely related to the dampening of electromechanical low‐frequency oscillations (ELFOs). These ELFOs must be dampened appropriately to maintain the stability and reliability of the system. However, it is relatively difficult to resolve the problem of ELFOs completely with traditional power system stabilizers (PSSs). Consequently, research should be directed towards the development of efficient damping controllers, or PSSs, for power oscillation damping. Motivated from the aforementioned fact, this article presents the design of a proportional integral derivative power system stabilizer (PID‐PSS) via a long short‐term memory neural network (LSTM) based deep neural approach for damping power system oscillations in interconnected power systems. LSTM is used to train the parameters of PID‐PSS. To evaluate the performance of the proposed LSTM based PID‐PSS, diverse test cases under different operating conditions are examined. Further, the performance of the proposed LSTM based PID‐PSS is compared with traditional PSSs through time‐domain simulations. The test cases reveal the desired efficiency achieved by the proposed LSTM based PID‐PSS under diverse loading conditions.

In this paper, the authors are willing to find the optimal and robust design for power system stabilizers (PSSs) in a multi-machine power system. In this regard a new Meta heuristic method as Simulated Annealing (SA) is used. The PSS parameters are computed to assure maximum damping performance under different scenarios. A multi machine electric power system is used to illustrative the performance of proposed method. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results. Simulation results are carried out by numerical simulations on MATLAB software. Keywords: Multi Machine, Power System Stabilizer, Low Frequency Oscillations, Simulated Annealing

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

Design of an adaptive bilinear power system stabilizer

This paper proposes a design of robust power system stabilizer (RPSS) based on inverse additive perturbation optimization in an interconnected power system with wind farms. In the design, system uncertainties are represented by the inverse additive model. The robust stability condition is used to form the optimization problem of PSS parameters. The structure of PSS is a conventional second-order lead-lag controller. The genetic algorithm is applied to solve the problem and achieve the PSS parameters. Simulation studies in the two-area four-machine system with wind farms confirm that the damping effect and robustness of the proposed PSS are superior to those of the compared PSS.

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort. Key words: Power system stabilizer (PSS) design, particle swarm optimization, power system dynamics, time-varying acceleration coefficients.

This paper aims to present the design of power system stabilizer (PSS) as a second-order sliding mode controller (SOSMC). Power systems have always been growing into more dynamic and complex systems. This is because of continuously occurring disturbances and parametric uncertainties in power systems due to changing loads. One of the major problems with this area is small frequency oscillations which lead to the system instability if these oscillations are not damped properly and also reduce power transfer capability. Therefore, it is essential to use power system stabilizers (PSS) to damp out small frequency oscillations. In this paper, single machine infinite bus (SMIB) system is used as study system. Sliding mode control (SMC) is a nonlinear and very robust control technique. Advantages of this controller can be used to control the power systems in order to increase the stability. But SMC has a major disadvantage of chattering. SOSMC overcomes the disadvantages produced by SMC. Therefore, in this paper, PSS is designed as SOSMC using twisting algorithm and applied to SMIB. The robustness of PSS as SOSMC is demonstrated by carrying out comparative simulation under different operating conditions of the SMIB power system.

In this paper a robust method is presented for the combined design of STATCOM and Power System Stabilizer (PSS) controllers in order to enhance the damping of the low frequency oscillations in power systems. The combined design problems among PSS and STATCOM internal ac and dc voltage controllers has been taken into consideration. The equations that describe the proposed system have been linearized and a Fuzzy Logic Controller (FLC) has been designed for the PSS. Then, the Particle Swarm Optimization technique (PSO) which has a strong ability to find the most optimistic results is employed to search for the optimal STATCOM controller parameters. The proposed controllers are evaluated on a single machine infinite bus power system with the STATCOM installed in the midpoint of the transmission line. The results analysis reveals that the combined design has an excellent capability in damping a power system's low frequency oscillations, and that it greatly enhances the dynamic stability of power systems. Moreover, a system performance analysis under different operating conditions and some performance indices studies show the effectiveness of the combined design.

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.

An evolutionary algorithm-based power system stabilizers (PSS) design for low-frequency oscillations (LFO) damping in multi-machine power system networks (MMPSNs) is presented in this paper. A damping ratio-based objective function is developed to enhance the system damping where the widely employed lead-lag type PSS is considered in the problem formulation. The equilibrium Optimizer (EO), a recently developed metaheuristic algorithm that is capable of finding optimal solutions in complex engineering problems, is employed in this article. The algorithm's resilience is demonstrated by its ability to lead to the best PSS design regardless of the initial assumption made by the user. Two distinct multi-machine networks 2-area 4-machine and IEEE 10-machine 39-bus are used in this research. EO-based PSS results are compared with traditional PSS results to investigate which one yields better results for stability. According to the simulation findings, the EO technique reduces the settling time and overshoot significantly over the other techniques.

Design of Robust Power System Stabilizer in an Interconnected Power System with Wind Power Penetrations

Effects of various power system stabilizers on improving power system dynamic performance

In the category of small signal stability problem, one of the major causes of unpredictability of power transfer in the inter-connected power system is due to low frequency oscillations (LFO). These oscillations in the inter-connected power system, affects the power transfer capability and thereby, needed to be suppressed. To damp the oscillation and protect the power system, power system stabilizers are used. In this study, a Kho-Kho optimization (KKO) based proportional integral derivative (PID) power system stabilizer is put forward which can suppress the LFO in the inter-connected power system. Optimization methods are widely being used to solve number of optimization problem. Therefore, in this work the specification of the stabilizer are calibrated using KKO technique by optimizing a objective function constructed using the Integral time square error (ITSE) of the speed deviation. To test the effectiveness of the designed optimal controller, a one machine infinite bus (OMIB) with IEEE type DC-1 exciter unit is also taken into consideration. The superiority of the proposed technique is examined by comparing the obtained results with some other existing techniques.

The coordinated design of power system stabiliser (PSS) and a static synchronous compensator (STATCOM)-based controller for power system stability improvement is presented in this paper. The design problem is formulated as a parameter constrained, simulation-based, non-linear optimisation problem and bacteria foraging optimisation algorithm (BFOA) is employed to determine the optimal controller parameters. The performance of the proposed controllers is evaluated and compared with a conventional power system stabiliser (CPSS) in a single-machine infinite-bus power system subjected to various transient disturbances. The non-linear simulation results show that the proposed coordinately designed STATCOM-based controller and PSSs improve greatly the system damping and are robust to variation in operating conditions and fault clearing sequence. Finally, the coordinated design problem is extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed BFOA-optimised controllers.

It is very important to take into consideration time delay in wide area power system stability; the design of PSS (Power System Stabilizer) should consider global optimization with WAMS (Wide Area Measurement System) time delay. Newly designed PSS should be insensitive to time delay and suppress internal low frequency oscillations. It is used as feedback signal and is real-time synchronous that WAMS signal shows. Power system is modeled with the consideration of time delay. LMI (Linear Matrix Inequalities) is used to solve the stability condition of time delay system. Based on the time-delay effect of the wide-area measurement signals, this paper redesigned the PSS with global optimization of power system. The attached two-area-four-machine system simulation illustrates that wide-area PSS designed by global optimization with the consideration of time-delay can limit internal low frequency oscillation with time-delay insensitivity, and improve the stability of power system. It implements global optimization of PSS with WAMS time delay stability.