Abstract
Maximum power point tracking (MPPT) is one of the key functions of the solar power management system in solar energy deployment. This paper investigates the design of fuzzy-logic-based solar power MPPT algorithms using different fuzzy input variables. Six fuzzy MPPT algorithms, based on different input variables, were considered in this study, namely (i) slope (of solar power-versus-solar voltage) and changes of the slope; (ii) slope and variation of the power; (iii) variation of power and variation of voltage; (iv) variation of power and variation of current; (v) sum of conductance and increment of the conductance; and (vi) sum of angles of arctangent of the conductance and arctangent of increment of the conductance. Algorithms (i)–(iv) have two input variables each while algorithms (v) and (vi) use a single input variable. The fuzzy logic MPPT function is deployed using a buck-boost power converter. This paper presents the details of the determinations, considerations of the fuzzy rules, as well as advantages and disadvantages of each MPPT algorithm based upon photovoltaic (PV) cell properties. The range of the input variable of Algorithm (vi) is finite and the maximum power point condition is well defined in steady condition and, therefore, it can be used for multipurpose controller design. Computer simulations are conducted to verify the design.
Highlights
Solar power is one of the most cleanest and abundant energy source in the world
This paper summarized the designs of six fuzzy maximum power point tracking (MPPT) algorithms using different input variables
Determinations of the fuzzy rules associated with the different fuzzy input variables, as well as the advantages and disadvantages of the algorithms have been summarized in the paper
Summary
Solar power is one of the most cleanest and abundant energy source in the world. It is virtually inexhaustible and is likely to be our main source of power in the future [1,2]. Fuzzy controllers are able to use empirical methods or professional knowledge to design variable step size increments of duty ratio command for the power converter even without having an understanding of the mathematical model of the plant. Design considerations and effectiveness of the fuzzy MPPT algorithm depend on the input and output variables selected for the system. The output variable of the fuzzy MPPT algorithm would usually be the duty ratio command of the power switch for the power converter. The most commonly used input variables for the MPPT algorithms would be the slope of the power-versus-voltage (P-V) curve of the PV cell characteristics curves and changes of this slope [10,11,12,17]. Algorithm (vi) could be formulated as a means of feedback control and applied in multipurpose controller designs
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