Abstract
This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generator (SEIG). The aim of the developed control method is to automatically tune and optimize the scaling factors and the membership functions of the Fuzzy Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated voltage source PWM converters with a carrier-based Sinusoidal PWM modulation for both Generator- and Grid-side converters have been connected back to back between the generator terminals and utility grid via common DC link. The indirect vector control scheme is implemented to maintain balance between generated power and power supplied to the grid and maintain the terminal voltage of the generator and the DC bus voltage constant for variable rotor speed and load. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and also machine parameters mismatches. The proposed control scheme has improved the voltage regulation and the transient performance of the wave energy scheme over a wide range of operating conditions.
Highlights
Producing energy from renewable energy resources such as solar, wind, ocean, micro-hydro, biomass, etc. is becoming a necessity because of the continuous increasing of world energy demand of electrical power and continuous depreciation of conventional energy resources like oil, gas and coal
This paper has presented the modeling and simulation of wave energy driven self-excited induction generator which feeds power to the utility grid
The adaptive fuzzy tuning control strategy was applied to the sliding mode controller for adopting the controller parameters according to the tracking error to both the dc-link voltage and ac line voltage regulation
Summary
Producing energy from renewable energy resources such as solar, wind, ocean, micro-hydro, biomass, etc. is becoming a necessity because of the continuous increasing of world energy demand of electrical power and continuous depreciation of conventional energy resources like oil, gas and coal. This paper describes the application of the MOGA and MOPSO for the automatic design of the scaling factors and the membership function parameters of a Mamadani-type fuzzy sliding mode control system in order to find the best intelligent controller associated to the flux oriented control technique for a variable speed wave turbine driven SEIG interfaced to the grid. A number of fitness functions are defined to measure the performance of the proposed controllers such as minimizing the mean square errors of the DC voltage, DC current, the Root Mean Square (RMS) of the AC line voltage and the frequency Since these objectives are conflicting, multi-objective optimization is used to find a Pareto front from which a desired optimal operating state can be chosen.
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