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An autonomous power generation system (APGS) contains units such as diesel energy generator, solar photovoltaic units, wind turbine generator and fuel cells along with energy-storing units such as the flywheel energy storage system and battery energy storage system. The components either run at lower/higher power output or may turn on/off at different instants of their operation. Due to this, the conventional controllers will not provide desired performance under varied load conditions. This paper proposes an adaptive fuzzy logic PID (AFPID) controller for load frequency control. In order to achieve an improved performance, a modified whale optimization algorithm (mWOA) was also proposed in this paper for tuning of the AFPID parameters. The proposed algorithm was first evaluated using standard test functions and compared with other recent algorithms to authenticate the competence of algorithm. The proposed mWOA algorithm outperforms PSO, GSA, DE and FEP algorithms in five out of seven unimodal test functions and four out of six multimodal test functions. The effectiveness of the AFPID compared with the conventional PID and the proposed AFPID provides better performance. Reduction of 39.13% in error criteria (objective function) compared with WOA-PID controller. The proposed approach was also compared with some recently proposed frequency control approaches in a widely used two-area test system.

Summary The indeterminate characteristics of solar, wind sources, and load make modern AC microgrids highly complex and cause frequency fluctuations. It is very much required to maintain power equilibrium among generation and demand by planning a suitable frequency regulation controller. Henceforth, this research presents a maiden application of a hybrid Harris hawks optimization and pattern Search s (hHHO‐PS)‐based type‐2 fractional order fuzzy PID (T2FFOPID) controller for frequency regulation of an AC microgrid. Initially, a PID controller is considered, and the effectiveness of hHHO‐PS technique is compared with original Harris hawks optimization (HHO) as well as genetic algorithm (GA) and particle swarm optimization (PSO) techniques. In the next stage, superiority of proposed T2FFOPID over PID, type‐1 fuzzy PID (T1FPID), and fuzzy fractional order PID (T1FFOPID) controller is demonstrated. To authenticate the effectiveness of the suggested control method, different load disturbances as well as various rates of solar and wind sources penetration have been considered. The suggested control approach displays significant improvement in dynamic responses with fast damping of oscillations. Investigations of results affirm the better performance of T2FFOPID over other controllers regarding minutest error criteria and undershoot/overshoot of frequency deviations at various disturbances. Additionally, sensitivity analysis validates the robust conduct of T2FFOPID controller under variations parameters and communication delay. Finally, the MATLAB simulation results are validated in the OPAL‐RT OP5700 RCP/HIL FPGA real‐time simulator for practical feasibility of the proposed work.

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An epic topology of PV system for 1Ф grid tied framework with high gain altered Re Boost Luo converter is developed. In this epic topology, the PV (Photovoltaic) system is connected with single phase network via a Re Boost Luo converter and Voltage Source Inverter. The voltage variance issues of PV framework are overwhelmed by extricating most extreme power from the array. The Whale Optimization is utilized to extract the vast majority of the power from photovoltaic array. Similar to the existing topology, the proposed scheme is designed using reference casings of direct and quadrature hub components. The Re Boost Luo converter acquires the benefits contrasted with traditional DC-DC converter scheme. The Whale Optimization Algorithm based closed loop control logic gives magnificent execution under different testing conditions and the results are compared with Fuzzy based calculation. The PWM (Pulse Width Modulation) generator is utilized for triggering the inverters and converter. The Re boost Luo converter switches are made from silicon carbide to diminish the exchanging misfortunes better than traditional switches. Unfaltering state and momentary reaction of the controller are examined to know the excellence of the proposed novel system. Thus a high voltage gain is attained through the proposed converter and control algorithm. The grid current synchronization is accomplished via ANN (Artificial Naural Natwork) controller so that the THD (Total Harmonic Distortion) is reduced to fulfill the IEEE standard. Thus the proposed framework decreases the power quality issue of 1Ф grid system fed by the PV system. The outcomes are verified with Matlab recreation tool and DSPIC30F2010 controller.