Abstract
This paper deals with the implementation and analysis of a new maximum power point tracking (MPPT) control method, which is tested under variable climatic conditions. This new MPPT strategy has been created for photovoltaic systems based on Particle Swarm Optimization (PSO). The novel Improved Particle Swarm Optimization (IPSO) algorithm is tested in several simulations which have been implemented in view of the various system responses such as: voltage, current, and power. The performances of the proposed IPSO algorithm have been completed and compared with results of well-established methods adopted in the literature showing a higher accuracy.
Highlights
In recent years, solar energy has become one of the most popular renewable energy sources due to several advantages related to its availability and environmental sustainability [1,2,3]
The Improved Particle Swarm Optimization (IPSO) method was tested under a steep variation of the irradiance conditions, which is distributed over four intervals, while keeping the constant temperature equal to 25 ◦ C as indicated in Figure 9 which are the same conditions found in literature [30,31]
The method presented here is based on the search for the maximum point and the algorithm performance strongly depends on the shape of the fitness function and does not depend on the absolute values characterizing it
Summary
Solar energy has become one of the most popular renewable energy sources due to several advantages related to its availability and environmental sustainability [1,2,3]. Algorithms [13], and Particle Swarm Optimization (PSO) [14] These MPPT algorithms differ in many features such as their complexity and the resulting computational burden, their steady state accuracy and efficiency, their range of effectiveness, their tracking speed, and their ability to track the MPP under changing environmental conditions and partial shading. The here proposed Improved Particle Swarm Optimization (IPSO) method is mainly affected by the determination of the correct duty cycle based on a mixed metric This metric is able to converge the PV system towards the MPP under an environmental conditions change (especially shading conditions) and guarantee the highest accuracy. The paper is organized as follows: Section 2 illustrates the modeling and the fundamental characteristics of the PV system used to test the proposed IPSO, Section 3 explains the IPSO algorithm, and Section 4 analyzes simulation results
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