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IntroductionStability of nominal frequency and voltage level in an electric power system is the primary control issue of practicing engineers. Any deterioration in these two parameters will affect the performance and life expectancy of the associated machinery to the power system. In power system, controllers are installed and set for a specific working situation and deal with small variations in load demand to keep the frequency and terminal voltage magnitude within the permissible limits. Therefore, two numbers of loops are provided for each generator. The load frequency control (LFC) loop regulates the real power and frequency, whereas the automatic voltage regulator (AVR) loop takes care of the reactive power and voltage magnitude [1,2]. Earlier, researchers have done a study Abstract Stability of nominal frequency and voltage level in an electric power system is the primary control issue of practicing engineers. Any deterioration in these two parameters will affect the performance and life expectancy of the associated machinery to the power system. Hence, controllers are installed and set for a specific working situation and deal with small variations in load demand to keep the frequency and terminal voltage magnitude within the permissible limits. As the system performance can be improved with selecting suitable controller, an attempt has been made to design fractional-order PID (FOPID) controller for combined frequency and voltage control problems. This paper presents plan and execution examination of FOPID controller for simultaneous load frequency and voltage control of power system using recently developed nature-motivated powerful optimization technique, i.e., moth flame optimization algorithm. The first part of the present work demonstrates the implementation of the proposed technique on frequency stabilization of isolated power system with AVR for excitation voltage control. The superiority and effectiveness of the proposed approach are tested by comparing the dynamic response of the system with PID controllers optimized by other intelligent techniques. Then the present work is extended to multi-unit two-area power system. The tuning ability of the algorithm is extensively and comparatively investigated.

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