Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm
To achieve the goal of achieving carbon-neutral by 2060, the government of China has put forward higher requirements for energy conservation and consumption reduction in the energy industry. Therefore, it is necessary to reduce energy consumption in the process of transporting oil. In this paper, an...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/20/7453 |
| _version_ | 1797473563871019008 |
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| author | Shanbi Peng Zhe Zhang Yongqiang Ji Laimin Shi |
| author_facet | Shanbi Peng Zhe Zhang Yongqiang Ji Laimin Shi |
| author_sort | Shanbi Peng |
| collection | DOAJ |
| description | To achieve the goal of achieving carbon-neutral by 2060, the government of China has put forward higher requirements for energy conservation and consumption reduction in the energy industry. Therefore, it is necessary to reduce energy consumption in the process of transporting oil. In this paper, an optimization model that minimizes the total energy consumption of the entire pipeline system is proposed and the squirrel search algorithm (SSA) is used to solve the optimization model. Meanwhile, to improve the performance of the SSA, two strategies are proposed. One is the adaptive inertia weight strategy, and the other is the multi-group co-evolution strategy. The adaptive inertia weight can adjust the step size of the flying squirrels according to the difference of the objective function value and multi-group co-evolution is introduced to improve population diversity. The improved SSA is named multigroup coevolution-adaptive inertia weight SSA (MASSA). A total of 20 benchmark functions are used to test the performance of MASSA, including unimodal functions and multimodal functions. Compared with the other four algorithms, MASSA has better performance and convergence capabilities. In the case study experiment, an optimization model of the oil pipeline is built, which takes the minimum energy consumption of the whole pipeline as the objective function. Compared with the actual operating conditions, the electricity consumption optimized by MASSA decreases by 399,018.94 kgce, and the thermal energy dissipation decreases by 113,759.25 kgce. The total energy consumption is reduced by 512,778.19 kgce, which is 9.62%. These results indicate that the two improvement strategies are significant, and optimizing the operating parameters can reduce energy consumption. |
| first_indexed | 2024-03-09T20:18:13Z |
| format | Article |
| id | doaj.art-335ec416f7554e93a3aeb95c830f23e7 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T20:18:13Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-335ec416f7554e93a3aeb95c830f23e72023-11-23T23:54:54ZengMDPI AGEnergies1996-10732022-10-011520745310.3390/en15207453Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search AlgorithmShanbi Peng0Zhe Zhang1Yongqiang Ji2Laimin Shi3School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, ChinaChina Petroleum Pipeline Engineering Corporation, Langfang 065000, ChinaChina Petroleum & Chemical Co., Ltd. of North Branch, Zhengzhou 450006, ChinaZhejiang Zheneng Natural Gas Operation Co., Ltd., Hangzhou 310051, ChinaTo achieve the goal of achieving carbon-neutral by 2060, the government of China has put forward higher requirements for energy conservation and consumption reduction in the energy industry. Therefore, it is necessary to reduce energy consumption in the process of transporting oil. In this paper, an optimization model that minimizes the total energy consumption of the entire pipeline system is proposed and the squirrel search algorithm (SSA) is used to solve the optimization model. Meanwhile, to improve the performance of the SSA, two strategies are proposed. One is the adaptive inertia weight strategy, and the other is the multi-group co-evolution strategy. The adaptive inertia weight can adjust the step size of the flying squirrels according to the difference of the objective function value and multi-group co-evolution is introduced to improve population diversity. The improved SSA is named multigroup coevolution-adaptive inertia weight SSA (MASSA). A total of 20 benchmark functions are used to test the performance of MASSA, including unimodal functions and multimodal functions. Compared with the other four algorithms, MASSA has better performance and convergence capabilities. In the case study experiment, an optimization model of the oil pipeline is built, which takes the minimum energy consumption of the whole pipeline as the objective function. Compared with the actual operating conditions, the electricity consumption optimized by MASSA decreases by 399,018.94 kgce, and the thermal energy dissipation decreases by 113,759.25 kgce. The total energy consumption is reduced by 512,778.19 kgce, which is 9.62%. These results indicate that the two improvement strategies are significant, and optimizing the operating parameters can reduce energy consumption.https://www.mdpi.com/1996-1073/15/20/7453energy optimizationinverter pumpsquirrel search algorithmmulti-group co-evolutionadaptive inertia weight |
| spellingShingle | Shanbi Peng Zhe Zhang Yongqiang Ji Laimin Shi Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm Energies energy optimization inverter pump squirrel search algorithm multi-group co-evolution adaptive inertia weight |
| title | Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm |
| title_full | Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm |
| title_fullStr | Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm |
| title_full_unstemmed | Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm |
| title_short | Optimization of Oil Pipeline Operations to Reduce Energy Consumption Using an Improved Squirrel Search Algorithm |
| title_sort | optimization of oil pipeline operations to reduce energy consumption using an improved squirrel search algorithm |
| topic | energy optimization inverter pump squirrel search algorithm multi-group co-evolution adaptive inertia weight |
| url | https://www.mdpi.com/1996-1073/15/20/7453 |
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