Optimal design of digital rational approximations with -dependant coefficients to model the fractional order integrator of any arbitrary order , where epsilon (0, 1), is presented in this work. The analytical expressi...
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Optimal design of digital rational approximations with -dependant coefficients to model the fractional order integrator of any arbitrary order , where epsilon (0, 1), is presented in this work. The analytical expressions of the coefficients for the proposed fractional order digital integrators (FODIs) are derived by a two-step method: (a) the coefficients of FODIs for varying from 0.01 to 0.99 in steps of 0.01 are determined by a meta-heuristic optimisation algorithm called symbiotic organisms search (SOS) and (b) curve fitting is applied on the SOS-optimised coefficients to obtain their generalised expressions. Previous works dealing with the design of FODI based on various meta-heuristic optimisers have considered only a few specific fractional orders;hence, the practical usability of such designs is restricted. This gap provides the motivation for conducting this research. Design quality robustness and convergence consistency of SOS are extensively compared with three other well-known meta-heuristicalgorithms. The superior modelling accuracy of the proposed designs is justified by comparing with the recent literature. Simulation results validate the effectiveness of the proposed models as a fractional order proportional-integral controller.
To improve the frequency stability in an interconnected power system including renewable energy sources, the control actions need to be more robust and efficient. For this reason, this study proposes a new optimised p...
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To improve the frequency stability in an interconnected power system including renewable energy sources, the control actions need to be more robust and efficient. For this reason, this study proposes a new optimised proportional-integral-derivative (PID) controller coordinated with redox flow batteries (RFBs) for the enhancement of load frequency control (LFC) of power system concerning large penetration of wind power generation. The PID controller parameters were obtained using a recently developed meta-heuristic optimisation algorithm named Grey Wolf optimiser. To show the effectiveness of the proposed control strategy, the interconnected two-area IEE Japan East 107-bus-30-machine power system was investigated for the simulation. The system dynamic responses were obtained considering load change in area-1 and large wind farm integration in area-2. A comparative study of performance of the proposed strategy with some well-known optimisation techniques was performed. Furthermore, the sensitivity analysis of the proposed controller was also examined by varying the penetration range of the integrated wind farm. Dynamic responses obtained from the simulation satisfy the LFC requirements. In addition, the results reveal that the frequency control concept-based optimised PID controller coordinated with the RFB will enhance the frequency stability in terms of settling time, peak undershoot, and peak overshoot.
Parameter extraction of a solar cell is essential in the simulation and design calculation of photovoltaic (PV) systems. The mathematical model of the PV module is a non-linear I – V characteristic including several ...
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Parameter extraction of a solar cell is essential in the simulation and design calculation of photovoltaic (PV) systems. The mathematical model of the PV module is a non-linear I – V characteristic including several unknown parameters as the PV manufacturers’ data are not sufficient. This study presents a method for estimating the parameters of the single- and double-diode PV models of a PV module based on a nature-inspired meta-heuristic optimisation algorithm known as the whale optimisationalgorithm (WOA). The validity of the proposed WOA-based PV model is verified by comparing its simulation results with the experimental results for the PV modules under different environmental conditions.
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