Abstract
The load pressure on electrical power system is increased during last decade. The installation of new power generators (PGs) take huge time and cost. Therefore, to manage current power demands, the solar plants are considered a fruitful solution. However, critical caring and balance output power in solar plants are the highlighted issues. Which needs a proper procedure in order to minimize balance output power and caring issues in solar plants. This paper investigates artificial neural network (ANN) and hybrid boost converter (HBC) based MPPT for improving the output power of solar plants. The proposed model is analyzed in two steps, the offline step and the online step. Where the offline status is used for training various terms of ANNs in terms of structure and algorithm while in the online step, the online procedure is applied with optimum ANN for maximum power point tracking (MPPT) using traditional converter and hybrid converter in solar plants. Moreover, a detail analytical framework is studied for both proposed steps. The mathematical and simulation approaches show that the presented model efficiently regulate the output of solar plants. This technique is applicable for current installed solar plants which reduces the cost per generation.
Highlights
Based maximum power point tracking (MPPT) algorithm improve the quality of service of a solar power system; The model is designed for simulation analysis and is compared among various procedures like Elman neural network (ENN), with install hybrid boost converter (HBC) and artificial neural network (ANN) mechanisms and without install HBC and ANN procedures in order to evaluate proposed model executions; The proposed ANN model presents reliable outcomes in view of simple structure, fast training and robust performance
The results present that the ANN based photovoltaic generator (PVG) provide low oscillation and better performance
The ANN and HBC based MPPT is used for enhancing the productivity and performance
Summary
In order to fulfill power demands, installation of new power plants are time consumption and high expensive procedures [3] The renewable energies, such as wind and solar, appear to be appropriate solutions to cover energy demand while reducing environmental pollution and toxic materials [4]. In [8] the ANN technique is utilized for predicting droughts, in [9] the ANN method is studied for accurately measure the wind speed and predict its results, in [10] the particular matter is discussed for the Ankara city through ANN and in the field of solar system the ANN is applied in [11] for forecasting the generation of solar system
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