Abstract
Renewable sources have gained much attention due to fast-paced changes in the global industry, continuous fuel hikes, and depletion of fossil fuels. The hybrid renewable energy systems (HRES) provide a viable solution to the future power crisis. Optimal sizing is the key in the design of HRES. In this paper, the metaheuristic algorithm TLBO was proposed for the optimal sizing of the PV-Wind-Battery based grid-tied hybrid renewable energy system. The main objective is to determine the best suitable configuration of PV panels, wind turbines, and batteries such that LCE is minimized subject to reliability constraint GPAP, SSER, and maximizing renewable penetration to the grid while satisfying the load demand. An energy management system is applied for optimal coordination of renewable sources and full utilization of battery storage and also to ensure stable operation under variable power generation and load demand. The optimization has been performed for the whole year with a 1-h resolution. The obtained results confirm better performance in terms of effectiveness, accuracy, faster convergence, less computation time of the proposed algorithm when compared to PSO, Rao-1, Rao-2, Rao-3, GWO algorithms. The optimal system configuration has LCE of 0.1642 \$/kWh and GPAP, SSER of 0.0999, 0.1473 respectively. The LCE in a stand-alone system is 0.2104 \$/kWh, whereas, in a grid-connected system, it was reduced to 0.1642 \$/kWh for the same scenario. The results comparison revealed that the grid-connected HRES is more feasible than the stand-alone system.
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Bhimaraju, A., Bhanu Ganesh, G., Mahesh, A. (2024). Optimal Sizing of PV/Wind/Battery Grid-Connected Hybrid Renewable Energy Systems Using TLBO Algorithm. In: Mahajan, V., Chowdhury, A., Singh, S.N., Shahidehpour, M. (eds) Emerging Technologies in Electrical Engineering for Reliable Green Intelligence. ICSTACE 2023. Lecture Notes in Electrical Engineering, vol 1117. Springer, Singapore. https://doi.org/10.1007/978-981-99-9235-5_2
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DOI: https://doi.org/10.1007/978-981-99-9235-5_2
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