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The high-concentration photovoltaic (HCPV) system uses high-magnification condenser lens to focus sunlight on the surfaces of group III–V photovoltaic (PV) cells. The PV cells can convert sunlight to electricity effectively. However, since the HCPV system includes PV cells and concentrating equipment, its components are more than those of general photovoltaic systems and are more prone to high cost and malfunctions. Bypass diodes are installed in the HCPV modules to prevent power consumption when they are shaded or damaged. The main purpose of this paper is to investigate the influence of bypass diodes on the HCPV modules and look for an optimal bypass diode configuration. In this research, the authors cooperated with Arima EcoEnergy Technologies Corp. whose HCPV products were used as references for modeling the simulation system. MATLAB/Simulink was used as the modeling tool to establish a HCPV simulation system using the built-in PV cell model. Simulations were implemented under different shaded conditions and investigated the effects of power generations under different bypass diode configurations. According to the simulation results, the configuration of 1 bypass diode per 2 PV cells is the best in general and random shaded conditions; however, the configuration of 1 bypass diode per 3 and 6 PV cells are better for some special conditions. The simulation results in this paper can be provided to HCPV companies as references, while designing products in the future, and should be helpful for improving performance and cost of the products.

The purpose of this paper is to compare three power-feedback maximum power point tracking (MPPT) algorithms used in photovoltaic systems. The Matlab/Simulink is used in this paper to establish a model of photovoltaic system with MPPT function. This system is developed by combining the models of established PV module and DC-DC boost converter with the power-feedback MPPT algorithms of perturbation and observation, incremental conductance and hill climbing, respectively. The system will be simulated under different weather conditions and MPPT algorithms. According to the comparisons of the simulation results, it can be observed that the photovoltaic simulation system can track the maximum power accurately using the three MPPT algorithms discussed in this paper. HC algorithm possesses fast dynamic response, but P&O algorithm is well regulated PV output voltage and power than HC algorithm. The tracking time spent by INC algorithm is a little longer than the other two algorithms. The HC algorithm is suitable for the cases of battery charging which doesn't need extremely stable voltage, and the P&O algorithm is more suitable for the system with precision electric instruments. Furthermore, the INC algorithm is adaptable to the cases of fast changing weather conditions owing to its advantage of no misjudgment.

The purpose of this chapter is to establish a photovoltaic simulation system using mixed programming with LabVIEW and Simulink and compare the simulation results of three maximum power point tracking (MPPT) algorithms for the photovoltaic simulation system. The Matlab/Simulink is used in this chapter to establish the component models of the proposed photovoltaic simulation systems. LabVIEW is responsible for developing the virtual control interface and connects it with Simulink to perform simulation and analysis tasks. The proposed photovoltaic simulation system is developed by combining the models of solar modules and DC-DC boost converter with the tracking algorithms of perturbation and observation (P&O), incremental conductance (INC), and hill climbing (HC), respectively. The system will be simulated and analyzed under different weather conditions and MPPT algorithms. The simulation results will be shown on the interface of LabVIEW by mixed programming method. According to the comparisons of the simulation results, it can be observed that the photovoltaic simulation system can track the maximum power accurately using the three different MPPT algorithms, respectively. The simulation results can also be successfully displayed on the LabVIEW interface. The correctness and feasibility of the proposed photovoltaic simulation system is then validated.

The purpose of this paper is to forecast the electrical energy generated by photovoltaic systems using the method of neural network. A database, which includes the actual measured electrical energy and the parameters of weather conditions that can influence the electrical energy generated by the photovoltaic system (PV system), is established in advance in order to be used in electrical energy forecasts. The Matlab/Simulink software is used in this paper to set up a neural network model with the learning algorithm of back-propagation network in order to forecast the generated electrical energy of the PV system. After observing the results of electrical energy forecast and divergence evaluation, it can be found that the proposed neural network model can accurately forecast the generated electrical power and output current under different weather conditions. The feasibility and accuracy of the proposed forecast system is then validated.

The main purpose of this paper is to develop a photovoltaic simulation system with maximum power point tracking (MPPT) function using Matlab/Simulink software in order to simulate, evaluate and predict the behaviors of the real photovoltaic system. A model of the most important component in the photovoltaic system, the solar module, is the first to have been established. The characteristics of the established solar module model were simulated and compared with those of the original field test data under different temperature and irradiance conditions. After that, a model of a photovoltaic system with maximum power point tracker, which was developed using DC-DC buck-boost converter with the perturbation and observation method, was then established and simulated. According to comparisons of the simulation results, the I–V curves of the established solar module model could closely match those of the original field test data, and the model of the photovoltaic system that was built in this paper can track the maximum power point of the system successfully and accurately under arbitrary temperature and irradiance conditions. The accuracy and practicability of the photovoltaic simulation system proposed in this paper are, therefore, validated.