Advanced Energy Technologies
Hassan Z. Al Garni; Arunachalam Sundaram; Anjali Awasthi; Rahul Chandel; Salwan Tajjour; Shyam Singh Chandel
Abstract
A major design challenge for a grid-integrated photovoltaic power plant is to generate maximum power under varying loads, irradiance, and outdoor climatic conditions using competitive algorithm-based controllers. The objective of this study is to review experimentally validated advanced maximum power ...
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A major design challenge for a grid-integrated photovoltaic power plant is to generate maximum power under varying loads, irradiance, and outdoor climatic conditions using competitive algorithm-based controllers. The objective of this study is to review experimentally validated advanced maximum power point tracking algorithms for enhancing power generation. A comprehensive analysis of 14 of the most advanced metaheuristics and 17 hybrid homogeneous and heterogeneous metaheuristic techniques is carried out, along with a comparison of algorithm complexity, maximum power point tracking capability, tracking frequency, accuracy, and maximum power extracted from PV systems. The results show that maximum power point tracking controllers mostly use conventional algorithms; however, metaheuristic algorithms and their hybrid variants are found to be superior to conventional techniques under varying environmental conditions. The Grey Wolf Optimization, in combination with Perturb & Observe, and Jaya-Differential Evolution, is found to be the most competitive technique. The study shows that standard testing and evaluation procedures can be further developed for comparing metaheuristic algorithms and their hybrid variants for developing advanced maximum power point tracking controllers. The identified algorithms are found to enhance power generation by grid-integrated commercial solar power plants. The results are of importance to the solar industry and researchers worldwide.
Renewable Energy Economics, Policies and Planning
Seyed Mohammad Emami Razavi; Mohammad Hossein Jahangir; Soroush Mousavi
Abstract
The renewable energy can be utilized to satisfy the energy demand. Moreover, the solar energy as the most abundant energy resource among renewable energies plays a crucial role to provide the energy demand. The BIPV (building integrated photovoltaics) systems can be considered to supply the required ...
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The renewable energy can be utilized to satisfy the energy demand. Moreover, the solar energy as the most abundant energy resource among renewable energies plays a crucial role to provide the energy demand. The BIPV (building integrated photovoltaics) systems can be considered to supply the required energy demand from renewable sources. The essential advantage of BIPV systems is that they can be utilized as building component such as roof, window, shading systems and building façade and they can generate electricity simultaneously. Even though the photovoltaic technologies have been improved within past few years, however the utilization of the BIPV systems will be considered expensive. For this reason, the payback period calculation is considered a vital parameter in evaluating the BIPV systems. In this study, the overall energy consumption for producing one m2 of a mono-crystalline photovoltaic module is calculated 1334 kWh. Additionally, the photovoltaic module data for three companies were investigated and the annual energy productions for one m2 of each company’s product were obtained. The results showed that the average energy payback time for 270 and 280 watt modules are 5.565 and 5.254 respectively. Moreover, the energy payback time for 290, 325 and 340 watt modules were calculated 4.903, 5.437 and 4.965 respectively.
