Frequency control of autonomous hybrid power system using smart controllable load

In recent years, penetration of renewable energy technologies in electrical power systems have increased the system complexity and therefore require efficient controlling methods to ensure stable operation of the whole system. In present study, the frequency control of autonomous hybrid power system consisting of various generators such as wind turbine generator, diesel engine generator, fuel cell and solar photovoltaic is investigated in integration with aqua electrolyzer and smart controllable water heater. The intermittent nature of wind and solar power may cause a serious problem of frequency fluctuation. Therefore, a new robust PID controller with filtering technique (PIDF) has been designed for the proposed system to minimize the frequency deviation to zero. Proposed controller is provided with derivative filter to improve the performance when there is noise or random error in the measured process variables. Nature-inspired firefly algorithm (FA) based optimization is employed to search for optimal controller parameters and the corresponding dynamic performance are compared with conventional PI controller. Initially investigation has been carried out considering 1% step load perturbation (SLP) and then against random load pattern. Furthermore, performance of proposed controller against random variation of wind input power has been tested. Critical investigation reveal that firefly optimized PIDF controller is far superior to conventional PI controller in terms of settling time, reduced overshoots, undershoots and oscillation.