International Journal of Frontiers in Engineering Technology, 2024, 6(4); doi: 10.25236/IJFET.2024.060419.
Zhijie Cai1, Shihao Zuo2
1School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
2College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
In the domain of renewable energy, the pronounced variability inherent in wind and solar power generation poses substantial challenges to the stable functionality of electrical grids. This study acknowledges the significant variability inherent in wind and solar energy, which can affect the stability of power grids. This paper proposes a comprehensive model that integrates Copula sampling, K-means and hierarchical clustering, and Particle Swarm Optimization (PSO) algorithms to analyze and optimize the performance of hybrid wind-solar-pumped storage systems. This model accurately captures the dependency structures between wind and solar outputs, using clustering techniques to classify diverse energy production scenarios. Additionally, this paper employs the PSO algorithm to address a multi-objective optimization problem, balancing both operational and environmental costs in hybrid wind-solar-pumped storage systems. This paper findings reveal notable improvements in reducing energy waste due to uncertainties in renewable resource availability and achieving lower operational costs through the optimization of the hybrid wind-solar-pumped storage system. This research provides insights into the sustainable integration of renewable energies into power grids, with a particular focus on economic and environmental benefits.
Wind-solar uncertainty, K-means clustering, Hierarchical clustering, Pumped storage systems, Energy management, Particle Swarm Optimization
Zhijie Cai, Shihao Zuo. Optimal System Analysis for Hybrid Wind-Solar-Pumped Storage Systems under Renewable Output Uncertainty. International Journal of Frontiers in Engineering Technology (2024), Vol. 6, Issue 4: 115-126. https://doi.org/10.25236/IJFET.2024.060419.
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