Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations
ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model f...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Editorial Department of Journal of Sichuan University (Engineering Science Edition)
2024-01-01
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| Series: | 工程科学与技术 |
| Subjects: | |
| Online Access: | http://jsuese.scu.edu.cn/thesisDetails#10.12454/j.jsuese.202400699 |
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| Summary: | ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model for cascade pumping stations was established with the goal of minimizing carbon emissions, and the Runge Kutta algorithm (RUN) was introduced to solve the model. What's more, aiming at the lack of quantitative sensitivity analysis in the optimal scheduling of cascade pumping stations, the Sobol global sensitivity method was employed to quantitatively analyze the influence of each sensitive parameter on the carbon emissions of the cascade pumping stations. To address the local optimization problem caused by insufficient initial population diversity and individuals easily falling into the system boundary in RUN, an improved Runge Kutta (TRUN) optimization scheduling method based on a Tent chaotic map was proposed.MethodsFirstly, the optimal scheduling model of the cascade pumping stations was established with the objective of minimizing carbon emissions. Secondly, the Sobol method was used to analyze the sensitivity of the head of each pumping station and the flow rate of each unit to the carbon emissions of cascade pumping stations, explore the quantitative impact of decision variables on the objective function. Thirdly, an optimized scheduling method based on TRUN was proposed. On the basis of inheriting the exploration characteristics of the RUN algorithm, a Tent chaos mapping was adopted by TRUN to strengthen the initial population exploration ability, thereby speeding up the convergence speed and enhancing the accuracy of the solution. Additionally, a Tent boundary mapping strategy was employed to regenerate the boundary value, resulting in improved the optimization efficiency of RUN. Six benchmark functions, including unimodal, multimodal and fixed dimension, were used to verify the performance and improvement strategies of TRUN. Finally, taking a three-stage pumping station as an example, the Sobol method was used to quantitatively determine the sensitivity sequence of its system parameters, and TRUN was used to get the optimal scheduling scheme of the cascade pumping stations.Results and Discussions The mean and standard deviation of six benchmark functions, including unimodal (Schwefel 2.21 (<italic>f</italic><sub>1</sub>), Rosenbrock (<italic>f</italic><sub>2</sub>)), multimodal (Schwefel (<italic>f</italic><sub>3</sub>), Rastrigin (<italic>f</italic><sub>4</sub>)), fixed dimension (Hartman (<italic>f</italic><sub>5</sub>), Shekel (<italic>f</italic><sub>6</sub>)), were calculated by TRUN, RUN, TPSO, PSO, TGA and GA algorithms. TRUN, RUN, TPSO, PSO, TGA and GA algorithms hitted 4, 2, 0, 0, 1 and 0 optimal solutions, respectively, which verified the superiority of the proposed TRUN algorithm and the feasibility of the improved strategy. On this basis, the Sobol global sensitivity method and optimization scheduling method based on TRUN were used to solve the optimization scheduling problem of a three-stage pumping station. The results showed that the sensitivity sequence of system parameters quantitatively determined by the Sobol method was as follows in descending order: the flow rate of each unit in the first level pumping station, the flow rate of each unit in the second level pumping station, the head of the first level pumping station, the flow rate of each unit in the third level pumping station, the head of the second level pumping station, and the head of the third level pumping station. The results could provide suggestions for the daily operation decision-making of the project. The TRUN algorithm was applied to the optimization scheduling research of cascade pump stations, and the results showed that TRUN had 67, 56 and 46 optimal values in 100 sets of comparison data for each single-stage pumping station, and the total number of optimal values had a clear advantage among the six algorithms, in the optimization results of single-stage pumping stations. In the optimization results of cascade pumping stations, compared with the current operating scenario, the scheme obtained by TRUN could reduce carbon emissions by 249 485 kg/a, which was better than the optimization results acquired via using RUN、TPSO、PSO、TGA and GA algorithms, confirming that the proposed algorithm was able to serve the optimization operation of cascade pump stations well.ConclusionsThe results demonstrated the proposed TRUN had excellent optimization performance. The proposed optimal scheduling method of cascade pumping stations based on TRUN could effectively improve the current operating efficiency of the system, and the efficiency of the optimization scheme calculated by TRUN was better than that obtained by RUN, TPSO, PSO, TGA and GA, which demonstrated that the improved algorithm could be applied to the scheduling decision-making of cascade pumping stations and had excellent solving performance. In addition, the Sobol global sensitivity method was used to quantitatively analyze the influence of each sensitive parameter on carbon emissions of the cascade pumping stations, which could provide a reference for daily operation decision-making of pumping station system. |
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| ISSN: | 2096-3246 |