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A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm

In recent years, the solar energy has become one of the most important alternative sources of electric energy, so it is important to operate photovoltaic (PV) panel at the optimal point to obtain the possible maximum efficiency. This paper presents a new optimization approach to maximize the electrical power of a PV panel. The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. First the dummy variables that have effect on the output power are classified into two categories: dependent and independent. The proposed approach is a multistage one as the genetic algorithm, GA, is used to obtain the best initial population at optimal solution and this initial population is fed to Lagrange multiplier algorithm (LM), then a comparison between the two algorithms, GA and LM, is performed. The proposed technique is applied to solar radiation measured at Helwan city at latitude 29.87°, Egypt. The results showed that the proposed technique is applicable.
- Zagazig University Egypt
- Zagazig University Egypt
Photovoltaic Arrays, PV System, Economics, Population, Macroeconomics, TJ807-830, Lagrange multiplier, Quantum mechanics, Renewable energy sources, Engineering, Artificial Intelligence, FOS: Mathematics, Machine Learning Methods for Solar Radiation Forecasting, Maximum power principle, Photovoltaic system, Maximum Power Point Tracking, Energy, Renewable Energy, Sustainability and the Environment, Physics, Mathematical optimization, Photovoltaic Maximum Power Point Tracking Techniques, Power (physics), Computer science, Algorithm, Photovoltaic Efficiency, Environmental health, Genetic algorithm, Electrical engineering, Physical Sciences, Computer Science, Photovoltaic Power, Solar Thermal Energy Technologies, Medicine, Multiplier (economics), Mathematics
Photovoltaic Arrays, PV System, Economics, Population, Macroeconomics, TJ807-830, Lagrange multiplier, Quantum mechanics, Renewable energy sources, Engineering, Artificial Intelligence, FOS: Mathematics, Machine Learning Methods for Solar Radiation Forecasting, Maximum power principle, Photovoltaic system, Maximum Power Point Tracking, Energy, Renewable Energy, Sustainability and the Environment, Physics, Mathematical optimization, Photovoltaic Maximum Power Point Tracking Techniques, Power (physics), Computer science, Algorithm, Photovoltaic Efficiency, Environmental health, Genetic algorithm, Electrical engineering, Physical Sciences, Computer Science, Photovoltaic Power, Solar Thermal Energy Technologies, Medicine, Multiplier (economics), Mathematics
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