Abstract
Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller Kp (proportional constant) and Ti (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation.
Highlights
Renewable energy sources such as wind turbines and photovoltaics (PV) have gained prominence in generating electricity due to environmental concerns
The results presented in [15] indicate that the fuzzy–genetic model more accurately estimates the monthly solar radiation than an artificial neural network (ANN) and neuro fuzzy model
solid oxide fuel cell (SOFC) active power controller is to deliver a power set by the reference (PFCref), which is generated from the power management module
Summary
Renewable energy sources such as wind turbines and photovoltaics (PV) have gained prominence in generating electricity due to environmental concerns. During grid-connected operation, the system should be managed well in order to coordinate power generation between PV and SOFC, and at the same time ensure that load demand is fulfilled. Similar work was carried out in [4], where two intermittent sources (PV and wind) along with a fuel cell were used to deliver DC load They employed fuzzy logic control to achieve maximum power tracking for wind and PV. A cuckoo-search-optimization-based fuzzy logic controller is developed in [17] to operate a hybrid system consisting of PV, battery and diesel generator in standalone mode. A power management algorithm is developed for a grid-connected PV-SOFC hybrid system, taking into consideration variation in the load and solar radiation. The simulation model of the grid-connected PV-SOFC was built in PSCAD software
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