Abstract
In the current scenario, providing continuous power supply and meeting the peak load demand are becoming the prime challenges in the power sector. The existing nonrenewable energy source causes global warming, environmental pollution, and inability to provide necessary clean power due to the presence of modern technology, population growth, domestic appliances, agriculture sectors, and interconnection of a number of nonlinear loads. This problem can be avoided using hybrid power generation. In this paper, the necessary power and peak demand are provided by inviting the integration of a grid-connected photovoltaic with battery storage hybrid system. The solar photovoltaic power is integrated with the DC link of a syncro converter through the boost converter. The switching control function of the boost converter is operated with an intelligent controller to step up the voltage and track the maximum power from the intermittent nature of solar photovoltaic system. The Radial Basis Function Neural (RBFN) network-based intelligent controller is utilized for tracking the smoothening of the maximum power under dynamic irradiance and temperature conditions. The battery storage system is connected to a DC link through an appropriate DC–DC converter. The battery storage system stabilizes the DC link voltage using a voltage droop control. The performance of the proposed system is simulated in a grid-connected mode under variable load conditions using MATLAB–SIMULINK software.
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Dharavath, R., Jacob Raglend, I. (2020). Intelligent Controller Based Solar Photovoltaic with Battery Storage System for Conditioning the Electrical Power. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1048. Springer, Singapore. https://doi.org/10.1007/978-981-15-0035-0_4
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DOI: https://doi.org/10.1007/978-981-15-0035-0_4
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