Manta ray foraging optimization algorithm-based load frequency control for hybrid modern power systems

The regulation of the frequency and line power flow in interconnected power networks is considered to be a key aspect of load frequency control (LFC). This article broaches a modern power network composed of three interconnected control areas including traditional generation units taking into account non-linearities, also renewable energy sources (RESs) and energy storage (ES) units are involved in the power grid paradigm. Two forms of RESs are included in the analysis, which are photovoltaic (PV) and wind power plants. In addition, the study framework involves three types of ES units, which are batteries of plug-in electric vehicles (PEVs), flywheel energy storage system (FESS) and capacitive energy storage system (CESS). In this analysis, LFC is accomplished by the use of proportional-integral-derivative (PID) controllers in the system control loops. A recent optimization algorithm called Manta Ray Foraging optimization (MRFO) is employed to obtain the optimal gain configuration of the controllers. Real site measurements are imported to the RESs involved in the study aiming to examine the proposed control scheme under realistic conditions. Compared with other rival algorithms, the effectiveness of the MRFO-based PID controller is validated. Simulation results confirm the efficacy of the proposed control scheme. The findings also ensure the role of ES units in optimizing the time-domain responses. The main contributions of this paper are applying a new metaheuristic optimization algorithm to solve the LFC problem and introducing a new criteria for judging the system performance in compliance with the harmonic spectrum of the responses in the frequency domain. The results of the simulation are retrieved through a MATLAB model.