The Economic Optimization of a Grid-Connected Hybrid Renewable System with an Electromagnetic Frequency Regulator Using a Genetic Algorithm
Year: 2025
Type: article
Abstract: This paper presents a multi-objective optimization approach for the design of a hybrid renewable energy generation system (HRES) composed of photovoltaic (PV) modules, wind turbine (WT), battery bank (BB), electromagnetic frequency regulator (EFR), and backup diesel generator. Hourly series of solar irradiance and wind speed were collected for the UFRN campus in Macau/RN/Brazil. Detailed modeling of each component (including temperature effects on PV, corrected power curve of WT, and battery SoC dynamics) and calculation of discounted cash flow for 20 years were developed. A Genetic Algorithm (GA) was customized with real representation, uniform crossover, and adaptive Gaussian mutation, including elitism. The optimal configuration, PV≈35kWp, WT=30kW, ESS≈200kWh, EFR=30kW, achieved net present value (NPV) of R$ 1.86 M in 2015 values (R$ 3.11 M in 2025) and discounted payback in approximately 9 years. Sensitivity analysis to tariffs, costs, and climate scenarios confirmed technical and economic robustness. Comparison with the 2015 reference project showed gains of up to 17% in NPV. The integration of EFR and the method employed increased the capture and quality of wind energy, reducing conversion and maintenance costs.
Source: Energies
DOI: 10.3390/en18164404
Language: English
Subfield: Energy Engineering and Power Technology
Field: Energy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G29316538
OpenAlex ID: W4413306167