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Article

Using Cellular Automata Approach to Optimize the Hydropower Reservoir Operation of Folsom Dam

1
Civil and Environmental Engineering Department, University of South Carolina, Columbia, SC 29208, USA
2
Land, Air, and Water Resources Department, University of California, Davis, CA 95616, USA
3
Department of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz, Ahvaz 6135783151, Iran
*
Author to whom correspondence should be addressed.
Academic Editor: Fi-John Chang
Water 2021, 13(13), 1851; https://doi.org/10.3390/w13131851
Received: 30 March 2021 / Revised: 7 June 2021 / Accepted: 25 June 2021 / Published: 2 July 2021
(This article belongs to the Section Water Resources Management, Policy and Governance)
While hydropower in California is one the main sources of renewable energy, population growth has continuously increased demand for energy. In addition, recent droughts reduced the amount of available water behind the hydropower dams to provide the water head needed to run the turbines in hydropower plants. A more sustainable alternative, instead of developing new infrastructure, is to enhance the daily operation of reservoirs to support hydropower generation. This study suggests a new optimal operation policy for Folsom Reservoir in California and hydropower plants, which maximizes hydropower generation and reduces flood risk. This study demonstrates the application of the cellular automata (CeA) approach to optimize the daily hydropower operation of Folsom Reservoir. The reservoir operation is a nonlinear problem, where the hydropower generation and elevation-area-storage functions are the main nonlinearity to accurately represent the daily operation of the system. Moreover, the performance of the CeA approach under two extreme climate conditions, wet and dry, was evaluated and compared to the operation during normal conditions. Results showed that the CeA approach provides more efficient solutions in comparison to the commonly used evolutionary optimization algorithms. For the size of the non-linear optimization problem designed in this study, CeA outperformed genetic algorithm for finding optimal solutions for different climate conditions. Results of CeA showed that although the annual average inflow to the reservoir during the dry period was about 30% less than the normal condition, CeA offered about a 20% reduction in average hydropower generation. The new operation policy offered by CeA can partly compensate for the loss of the snowpack in California’s Sierra Nevada under a warming climate. The approach and its outcomes support an informed decision-making process and provide practical reservoir operational guideline to remediate the adverse effects of hydroclimatic changes in the future. View Full-Text
Keywords: hydropower; cellular automata; Folsom Reservoir; reservoir optimal operation hydropower; cellular automata; Folsom Reservoir; reservoir optimal operation
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MDPI and ACS Style

Goharian, E.; Azizipour, M.; Sandoval-Solis, S.; Fogg, G. Using Cellular Automata Approach to Optimize the Hydropower Reservoir Operation of Folsom Dam. Water 2021, 13, 1851. https://doi.org/10.3390/w13131851

AMA Style

Goharian E, Azizipour M, Sandoval-Solis S, Fogg G. Using Cellular Automata Approach to Optimize the Hydropower Reservoir Operation of Folsom Dam. Water. 2021; 13(13):1851. https://doi.org/10.3390/w13131851

Chicago/Turabian Style

Goharian, Erfan, Mohammad Azizipour, Samuel Sandoval-Solis, and Graham Fogg. 2021. "Using Cellular Automata Approach to Optimize the Hydropower Reservoir Operation of Folsom Dam" Water 13, no. 13: 1851. https://doi.org/10.3390/w13131851

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