Abstract

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Highlights

  • The global warming and environmental deterioration are considered as a factor of supply and consumption of energy based on the fossil fuels

  • The hourly basis wind speed (m/s), irradiance (W/m2) and ambient temperature ( ̊C) levels are recorded by the Pakistan Meteorological Department (PMD)

  • For PV subsystem, the performance of Hermite wavelet embedded NeuroFuzzy indirect adaptive controller (HWNFC) is compared with indirect NeuroFuzzy Takagi-Sugeno-Kang controller (ITSKC), TSK controller (TSKC) and incremental conductance based PI controller (InCond-PI)

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Summary

Introduction

The global warming and environmental deterioration are considered as a factor of supply and consumption of energy based on the fossil fuels. For WECS, Optimal torque control (OTC) MPPT strategy is quite popular, as it extracts the optimum wind energy [3], [4]. SOFC is versatile, efficient and alternative energy source which generates electrical power directly from hydrocarbon fuels at 800–1000 ̊C. To address the load following issue of SOFC, different conventional and advanced control strategies are available. Model predictive control (MPC) is a predictive model and receding horizon optimization based feedback control system This is an attractive approach for SOFC, because, a wide-range constraints of input/output variables of a nonlinear system are directly handled [28]. The dynamic operation and control of PV, wind and SOFC based HPS is presented [32]. A novel operation and control strategy for a stand-alone HPS with battery storage is presented [37].

Problem formulation
VSWT-PMSG MPPT subsystem adaptive control design
PV MPPT subsystem adaptive control design
SOFC adaptive control problem
Supervisory control policy
Results and discussion
Conclusion
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