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This paper presents an effective concept for hybrid fuel cell-photovoltaic-wind-battery active power filter (FC-PV-Wind-Battery) energy scheme based on the variable structure sliding mode fuzzy logic controller (SMFLC) using the multiobjective particle swarm optimisation (MOPSO). The parameters of the fuzzy logic control membership functions and the weighting factors of the SMFLC can be tuned by MOPSO in such an approach to optimise the dynamic performance of the shunt active power filter (SAPF) and minimise the total harmonic distortion (THD) of the source current waveform and voltage waveform of the hybrid (FC-PV-Wind-Battery). A group of objective functions was chosen to validate the dynamic performance of the SAPF and the effectiveness of the MOPSO-SMFLC. These selected fitness functions are: (i) minimising the error of the inverter capacitor DC voltage, (ii) minimising the THD of the output current and voltage of DC and AC sides and (iii) minimising the controller reaching time. A computer simulation study using Simulink/Matlab and experimental laboratory prototype were carried on to asses and compare the dynamic performance of the proposed MOPSO-SMFLC controller with the conventional proportional-integral-derivative, variable structure SMFLC, the feed-forward multilayer neural network controller and the variable structure SMFLC based on the single-objective particle swarm optimisation.

This study presents the use of hybrid photovoltaic -fuel cell (PV -FC) renewable energy scheme for vehicle-to-grid (V2G) battery-charging stations. The hybrid PV -FC DC interface scheme is dynamically controlled using a self-regulating tri-loop controller based on multi-objective particle swarm optimisation. The proposed utilisation scheme ensures efficient DC source energy utilisation from the hybrid PV -FC DC with minimal DC current inrush conditions and a fully stabilised DC bus voltage. The multi-loop battery-charging regulator allows for hybrid (voltage, current and power) charging modes for efficient, fast charging and DC energy efficient utilisation. The proposed hybrid renewable green energy PV -FC battery-charging scheme is fully validated by simulation and laboratory prototype testing. Nomenclature PSOparticle swarm optimisation SOPSO single-objective particle swarm optimisation MOPSO multi-objective particle swarm optimisation FC fuel cell PV photo voltaic HEV hybrid electric vehicle GPFC green plug filter compensator V id velocity of the ith particle with d dimensions X id position of the ith particle with d dimensions rand 1 , rand 2 two uniform random functions on the range [0.1] v inertia weight that is chosen beforehand C 1 cognitive learning rate C 2 social learning rate P id location along dimension d at which the particle previously had the best-fitness measure P gd current location along dimension d of the neighbourhood particle with the best fitness V d instantaneous DC bus voltage V d base base value of the DC bus voltage I d instantaneous DC bus current I d base base value of the DC bus current T 12 , T 13 , T 14 time delays for the green plug filter compensator scheme regulator (B) V B instantaneous battery voltage

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