Optimal Maximum Power Point Tracking Research Articles

A novel improved particle swarm optimization maximum power point tracking control method for photovoltaic array by using current calculated predicted arithmetic under partially shaded conditions

First, a novel current calculated (CC) principle is discussed in the study of the characteristics of the photovoltaic (PV) array under partial shading irradiation conditions. In this paper, the particle swarm optimization maximum power point tracking (MPPT) control method integrates with the proposed current calculated method to realize the rapid and accurate tracking efficiency for PV power under partial shading conditions. The proposed CC method is used as a tool to study the effects of partial shading and distribution of multiple peaks. In addition, the combined MPPT method is easy to gain the global peak of multiple PV arrays at complex partial shading. The experimental and simulation results prove the availability as compared with the traditional Perturbation and Observation method.

A novel particle swarm optimization maximum power point tracking control method based on the direct current voltage superposition principle under partially shaded conditions

In this paper, a novel particle swarm optimization maximum power point tracking (MPPT) control method is presented to gain the maximum power point of photovoltaic (PV) power, which is based on the direct current voltage superposition principle to predict the output characteristic of a PV array at partial shading. The proposed control method conveniently can be used in the real-time MPPT control strategy for large-scale PV systems, and with the implementation of the collect circuit it is easy to gain the global peak of multiple PV arrays, thereby resulting in lower cost and higher overall efficiency. The proposed method is proved by using simulation results.

A Novel Combined Particle Swarm Optimization and Genetic Algorithm MPPT Control Method for Multiple Photovoltaic Arrays at Partial Shading

The output characteristics of multiple photovoltaic (PV) arrays at partial shading are characterized by multiple steps and peaks. This makes that the maximum power point tracking (MPPT) of a large scale PV system becomes a difficult task. The conventional MPPT control method was unable to track the maximum power point (MPP) under random partial shading conditions, making the output efficiency of the PV system is low. To overcome this difficulty, in this paper, an improved MPPT control method with better performance based on the genetic algorithm (GA) and adaptive particle swarm optimization (APSO) algorithm is proposed to solve the random partial shading problem. The proposed genetic algorithm adaptive particle swarm optimization (GAAPSO) method conveniently can be used in the real-time MPPT control strategy for large scale PV system, and the implementation of the collect circuit is easy to gain the global peak of multiple PV arrays, thereby resulting in lower cost, higher overall efficiency. The proposed GAAPSO method has been experimentally validated by using several illustrative examples. Simulations and experimental results demonstrate that the GAAPSO method provides effective, fast, and perfect tracking.

Particle Swarm Optimization MPPT Method for PV Materials in Partial Shading

Today, the large-scale Photovoltaic (PV) power system, connected to grid, is in their advanced development stage and is extremely interest in whole world. The real large-scale PV array can be partially shaded by the shadow of building, cloud, bird and dirt. The output characteristic of PV materials in partially shaded conditions is strong nonlinear, and there are multi local peaks in output power voltage curve, and the only one real peak exists in these local peaks. Certainly, the maximum power point tracking (MPPT) method is very important to extract the as much as possible energy from the costly PV materials. The variant weight Particle Swarm Optimization (PSO) method is proposed to track the real peak by using the excellent multi-peak value optimization characteristic of PSO algorithm. The simulation results shows that the proposed PSO method can improve the response speed and output efficiency of PV materials in partial shading as compared to the conventional Incremental conductance (IC) method.