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In this paper, a student psychology-based optimization algorithm (SPBOA)-based proportional-integral-derivative (PID) controller is implemented for load frequency control (LFC) of an isolated hybrid power system (IHPS) and a grid-connected HPS (GHPS) models. In the designed models, a combined-cycle gas turbine, a diesel engine generator, a wind turbine generator and a solar photovoltaic generating unit are used as the main power generating units. A superconducting magnetic energy storage is used with IHPS model to improve the dynamic stability of the studied system. A single area power system is connected with IHPS model through a tie-line to form a GHPS. In the GHPS, a thyristor-controlled series controller and a unified power flow controller are associated with the tie-line power flow control. In this work, electric vehicle is also connected as a load to both the IHPS and GHPS models. The output profile of the proposed SPBOA-based PID controller of both models is compared with whale optimization algorithm (WOA) and quasi-oppositional-based WOA (QOWOA). The performance of IHPS and GHPS models are studied under the different load perturbations. The robustness analysis and frequency domain analysis in terms of Bode plot are also shown in favor of the SPBOA method.

Electric vehicle (EV) provides the most promising transportation system at present and also for the future. The uncertainties are introduced when EVs are connected to the grid, which becomes a new challenge for the load frequency control (LFC) of a power system. This paper explores the LFC of a hybrid power system (HPS) integrated with EV. The isolated HPS (IHPS) considered for this work consists of a combined cycle gas turbine (CCGT), a diesel engine generator (DEG), a wind turbine generator (WTG) and a solar photovoltaic generating unit. A superconducting magnetic energy storage is used to give uninterrupted power supply and to improve the dynamic stability to the system. The performance of charging and discharging of EV's battery is also analyzed. To enhance the performance of the EV, a proportional‐integral‐derivative (PID) controller is employed for controlling the pulse of the static switches. In concern with the LFC task, the PID controller is also used for WTG, CCGT, and DEG. The controller gains are tuned by the use of quasi‐oppositional whale optimization algorithm (QOWOA). The performance of IHPS model is studied under different load perturbations. A comparative dynamic response of frequency deviation profile is plotted subjected to QOWOA based PID controller.

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