In recent decades, renewable energy sources, such as wind power, have extraordinarily increased their participation in the energy mix throughout the world. This progression has played an important role in lowering the usage of fossil fuels. In addition, it has reduced environmental hazards and increased the emergence of hybrid power systems, mainly in remote areas. In some of these areas, diesel power plants were the only previous source of energy. Irrespective of the benefits, hybrid power systems might face problems such as frequency deviations. To contribute to reducing these problems, this paper presents a methodology to tune diesel engine governors using the Student Psychology-Based Algorithm. This proposed methodology enhances some metrics of controller performance, such as the integral square error, integral absolute error, and number of sign changes in the frequency derivative. This approach has been tested against different perturbations (step, ramp and random). To validate the effectiveness of the proposed approach, it has been simulated in relation to the San Cristobal Island (Ecuador) hybrid wind–diesel power system. The simulation results show that the governor tuned with the proposed approach provides a better system response.
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