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A comprehensive review on stability analysis in multimachine power system is presented in this study. The increasing demand of power has led to the expansion of power system and complexity in design as well as operation. This threatens to deteriorate the stability and reliability in the power network. However, with the advances in semiconductor and power electronic control technology, various flexible AC transmission systems (FACTS) are designed to enhance the power system stability. Different power system configurations with the incorporation of conventional and distributed generations (DGs) are proposed whose stability is being tested in the presence of the FACTS controllers. The optimal damping of power system oscillations under transient operating conditions are studied in presence of HVAC and HVDC links with conventional as well as DG systems and energy storage options like battery, supercapacitors and so on. Different control approaches such as classical control, robust control, wide-area control along with soft computing approaches like neural networks, fuzzy logic control, adaptive neurofuzzy inference system, genetic algorithm, particle swarm optimisation and so on are broadly discussed. A comparative analysis of different methodologies is presented to establish a quick survey of the proposed solutions for stability enhancement.

An adaptive fractional fuzzy sliding mode controller (AFFSMC) based power system stabilizer (PSS) is proposed for damping out low‐frequency oscillations in single machine infinite bus and multimachine power systems under various operational contingencies. The proposed stabilizer is a combination of adaptive fuzzy control with a fractional order proportional integral derivative controller and sliding mode controller. A fractional sliding surface is adopted which enables the system to remain in the proposed robust sliding surface stably to eliminate the effects of chattering at any initial conditions. In addition, fractional adaptive rules based on fuzzy sets were used for optimal selection of parameters of the controller. Here, the stability issue is addressed through Lyapunov synthesis. Speed deviation and acceleration are considered as input signals to the proposed controller. A comparative analysis of performance indices such as settling time, maximum peak overshoot is presented to demonstrate the advantages of the proposed approach. In addition, stability analysis using Eigen value, integral time absolute error and shape of demerit were also presented to augment the stability study. The simulation results confirm that the proposed AFFSMC‐PSS shows superior robust damping performance as compared to other approaches.

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