No abstract

Fault detection in solar photovoltaic (PV) arrays is a fundamental task to protect PV modules from damage and to eliminate risks of safety hazards. In this work, we show a new methodology for automatic supervision and fault detection of PV Systems, based mainly on optimal placement of sensors. This supposes the possibility to build a dynamic model of the system by using the bond graph tool, and the existence of a degradation model in order to predict its future health state. The choice of bond graph is motivated by the fact that it is well suited for modeling physical systems where several types of energies are involved. Fault behavior of PV arrays is highly related to the fault location, fault impedance, irradiance level, and use of blocking diodes. In this work, PV array is connected using series parallel (SP) and Total Cross Tied (TCT) configurations including sensors to measure voltage and currents. The simulation results show the importance of the approach applied for the detection and diagnosis of fault in PV system. These results have been contrasted with real measured data from a measurement campaign plant carried on electrical engineering laboratory of Grenoble using various interconnection schemes are presented.

This work aims to consider the combination of different technologies regarding energy production and management with four possible configurations. We present an energy management algorithm to detect the best design and the best configuration from the combination of different sources. This combination allows us to produce the necessary electrical energy for supplying habitation without interruption. A comparative study is conducted among the different combinations on the basis of the cost of energy, diesel consumption, diesel price, capital cost, replacement cost, operation, and maintenance cost and greenhouse gas emission. Sensitivity analysis is also performed.

The output power of the Photovoltaic system having multiple arrays is reduced to a great extent when it is partially shaded due to environmental hindrances. Conventional popular MPPT methods are effective under uniform solar irradiance. However, under partially shaded conditions, these MPPTs can fail to track the real MPP because of the multiple local maxima which can be existed on PV characteristic curve under partially shaded condition. This paper reports the development of a maximum power-point tracking method for photovoltaic systems under partially shaded conditions using bond graph. The major advantages of the proposed method are simple computational steps, faster convergence, and its implementation on a low-cost microcontroller. The performance of proposed MPPT is analyzed according to the position of real MPP. Simulation results have been contrasted with real measured data from a commercial PV module of Photowatt PW1650.

Traditional MPPT algorithms have demonstrated effective performance relative to their flexibility and simplicity of implementation. However, its main disadvantages are the ineffectiveness and the large oscillations around the MPP under non-uniform solar irradiance. To achieve better performance in the power extraction from the PV system, we propose in this work a new hybrid controller focused on the bond graph and fuzzy logic (BG-FL-MPPT) to track the maximum power point under different weather conditions. The aim of the research is BG-FL-MPPT development, which will guarantee the optimum power reference operation of the system with greater efficiency, less error in the stability and voltage fluctuations. A rigorous comparison was made between the developed controller and other two MPPT algorithms, including perturbation and observation (P&O) and particle swarm optimization (PSO), in three distinct test scenarios to check the effectiveness of the suggested control. In terms of stability and robustness, it was found from the results obtained that the established controller assures the required operation of the studied system by tracking efficiency of up to 99.95% to achieve the maximum power point. A 90% faster convergence rate is obtained with a decrease in oscillations of 94.95%. The experimental tests were performed using a high-performance experimental platform, and in the same metrological conditions, an in-depth comparison of the experimental results with the results obtained by simulation was made.