Study on the Annual Runoff Forecast Model of the Main Stream of Nanxi River Based on PSO-ANFIS

Authors

  • Huifang Guo Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China
  • Jian Meng Hangzhou Hydrology and Water Resources Monitoring Center, 310016, China
  • Hairong Huang Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China
  • Shixia Zhang Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China
  • Denghong Wang Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China

DOI:

https://doi.org/10.13052/spee1048-5236.4316

Keywords:

Nanxi river, hydropower, PSO-ANFIS, runoff prediction, prediction accuracy

Abstract

In 2021, Wenzhou adopted measures to restrict the use of electricity, and the shortage of electricity became an important factor affecting the production and life of Wenzhou. Nanxi River is one of the main rivers in Wenzhou City, and its water resources are very rich. According to the statistics of the water conservancy planning of the Nanxi River basin, there are 96 hydropower stations in the Nanxi River basin, with a total installed capacity of 152100 kW, accounting for 57% of the installed capacity. The development and utilization of the Nanxi River water resources can alleviate the power shortage in Wenzhou power grid to a certain extent. The development and utilization of hydropower are closely related to the runoff of the basin. The river runoff is mainly determined by rainfall, underlying surface and upstream inflow. River runoff is affected by many factors in the process of formation, so it is difficult to improve its prediction accuracy. In order to improve the prediction accuracy of the runoff of the main stream of the Nanxi River, this paper introduces the runoff prediction model of particle swarm optimization adaptive fuzzy inference system (PSO-ANFIS). ANFIS model has the advantages of applying fuzzy rules and the nonlinear approximation ability of neural network, but the antecedent parameters of ANFIS model are prone to fall into local optimization. In order to improve the generalization ability of the antecedent parameters of ANFIS model, the PSO algorithm of global optimization is introduced to optimize the antecedent parameters of ANFIS. Through the application of the example, it is found that the decision coefficient of PSO-ANFIS model in the simulation stage is 0.987, and the decision coefficient in the prediction stage is 0.856. This model can be applied in the annual runoff forecast. Through comparison with ANFIS model, it is found that PSO-ANFIS model has better prediction effect.

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Author Biographies

Huifang Guo, Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China

Huifang Guo obtained the doctor’s degree in hydrology and water resources from Hohai University in 2010 and the master’s degree in hydrology and water resources from Zhengzhou University in 2007. She is now engaged in teaching and scientific research in Zhejiang Tongji Vocational College of science and technology. Her main research interests are water resources system analysis, water ecological environment analysis, flood control and disaster reduction research, etc.

Jian Meng, Hangzhou Hydrology and Water Resources Monitoring Center, 310016, China

Jian Meng obtained the bachelor’s degree in Hydrology and Water resources from Hohai University in 2007. He is now working at Hangzhou Hydrology and Water Resources Monitoring Center, engaged in monitoring and analysis of hydrology and water resources. His main research interests include hydrology and water resources monitoring, hydrology and water resources analysis and calculation.

Hairong Huang, Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China

Hairong Huang, master, senior engineer/associate professor. At present, she is engaged in teaching and scientific research in Zhejiang Tongji Vocational College of Science and Technology. The main research direction is the analysis of river revetment materials.

Shixia Zhang, Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China

Shixia Zhang received the doctorate from Zhejiang University in 2008. She is currently engaged in teaching and scientific research in Zhejiang Tongji Vocational College of science and technology. Main research interests: municipal engineering design and management, water supply and drainage engineering technology, project cost preparation and review, watershed hydrological ecology and disaster prevention technology research, etc.

Denghong Wang, Zhejiang Tongji Vocational College of Science and Technology, CO 311231, China

Denghong Wang, associate professor, obtained a master’s degree from Zhejiang University of Technology. He is currently engaged in teaching and research work at Zhejiang Tongji Vocational College of Science and Technology. His research direction is water quality treatment research.

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Published

2023-12-24

How to Cite

Guo, H. ., Meng, J. ., Huang, H. ., Zhang, S. ., & Wang, D. . (2023). Study on the Annual Runoff Forecast Model of the Main Stream of Nanxi River Based on PSO-ANFIS. Strategic Planning for Energy and the Environment, 43(01), 133–150. https://doi.org/10.13052/spee1048-5236.4316

Issue

Section

New Technologies and Strategies for Sustainable Development