Improved Multi-objective Moth-flame Optimization Algorithm based on R-domination for cascade reservoirs operation
•A multi-objective model considering power generation, ecology and navigation is established.•A novel multi-objective evolutionary algorithm is proposed to solve the reservoir operation model.•Radar figures are used to evaluate the Pareto front of reservoir operation model with many objectives.•The...
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| Vydáno v: | Journal of hydrology (Amsterdam) Ročník 581; s. 124431 |
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| Hlavní autoři: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.02.2020
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| ISSN: | 0022-1694, 1879-2707 |
| On-line přístup: | Získat plný text |
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| Abstract | •A multi-objective model considering power generation, ecology and navigation is established.•A novel multi-objective evolutionary algorithm is proposed to solve the reservoir operation model.•Radar figures are used to evaluate the Pareto front of reservoir operation model with many objectives.•The relationships between power generation, ecology and navigation are analyzed.
Traditional power generation operation of reservoir mainly considers the maximization of power generation and guarantees the stability of the power system. However, blindly considering power generation objectives may ignore its impact on the ecological environment and navigation. A multi-objective optimization operation model considering power generation, ecological and navigation objectives is established in this paper. In order to efficiently solve the model, a new Improved Multi-objective Moth-flame Optimization Algorithm based on R-domination (R-IMOMFO) has been proposed. In order to enhance the ability of Moth-flame Optimization Algorithm (MFO) to overcome falling into the local optimum, it is improved from three aspects: update formula, inspiration of moth linear flight path and flame population update strategy, called improved MFO (IMFO) algorithm. In order to distinguish these individuals who are not dominated by each other in Pareto domination, the R-domination is proposed in combination with reference points. To verify the performance of IMFO and R-domination separately, different evolutionary algorithms and multi-objective mechanisms are combined to generate five new algorithms. Five new algorithms and five state-of-the-art algorithms are tested on the benchmark functions and reservoir operation model. The test results show that the proposed R-IMOMFO algorithm has the ability to obtain a set of solution with good convergence and strong distribution in the optimization operation problem of cascade reservoirs. Finally, the relationships between the objectives of the operation model are explored by the set of solution obtained by R-IMOMFO and the reason for the relationships is analyzed. The operation results show that the ecological demand and navigation demand have obvious contradictory relationships. |
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| AbstractList | Traditional power generation operation of reservoir mainly considers the maximization of power generation and guarantees the stability of the power system. However, blindly considering power generation objectives may ignore its impact on the ecological environment and navigation. A multi-objective optimization operation model considering power generation, ecological and navigation objectives is established in this paper. In order to efficiently solve the model, a new Improved Multi-objective Moth-flame Optimization Algorithm based on R-domination (R-IMOMFO) has been proposed. In order to enhance the ability of Moth-flame Optimization Algorithm (MFO) to overcome falling into the local optimum, it is improved from three aspects: update formula, inspiration of moth linear flight path and flame population update strategy, called improved MFO (IMFO) algorithm. In order to distinguish these individuals who are not dominated by each other in Pareto domination, the R-domination is proposed in combination with reference points. To verify the performance of IMFO and R-domination separately, different evolutionary algorithms and multi-objective mechanisms are combined to generate five new algorithms. Five new algorithms and five state-of-the-art algorithms are tested on the benchmark functions and reservoir operation model. The test results show that the proposed R-IMOMFO algorithm has the ability to obtain a set of solution with good convergence and strong distribution in the optimization operation problem of cascade reservoirs. Finally, the relationships between the objectives of the operation model are explored by the set of solution obtained by R-IMOMFO and the reason for the relationships is analyzed. The operation results show that the ecological demand and navigation demand have obvious contradictory relationships. •A multi-objective model considering power generation, ecology and navigation is established.•A novel multi-objective evolutionary algorithm is proposed to solve the reservoir operation model.•Radar figures are used to evaluate the Pareto front of reservoir operation model with many objectives.•The relationships between power generation, ecology and navigation are analyzed. Traditional power generation operation of reservoir mainly considers the maximization of power generation and guarantees the stability of the power system. However, blindly considering power generation objectives may ignore its impact on the ecological environment and navigation. A multi-objective optimization operation model considering power generation, ecological and navigation objectives is established in this paper. In order to efficiently solve the model, a new Improved Multi-objective Moth-flame Optimization Algorithm based on R-domination (R-IMOMFO) has been proposed. In order to enhance the ability of Moth-flame Optimization Algorithm (MFO) to overcome falling into the local optimum, it is improved from three aspects: update formula, inspiration of moth linear flight path and flame population update strategy, called improved MFO (IMFO) algorithm. In order to distinguish these individuals who are not dominated by each other in Pareto domination, the R-domination is proposed in combination with reference points. To verify the performance of IMFO and R-domination separately, different evolutionary algorithms and multi-objective mechanisms are combined to generate five new algorithms. Five new algorithms and five state-of-the-art algorithms are tested on the benchmark functions and reservoir operation model. The test results show that the proposed R-IMOMFO algorithm has the ability to obtain a set of solution with good convergence and strong distribution in the optimization operation problem of cascade reservoirs. Finally, the relationships between the objectives of the operation model are explored by the set of solution obtained by R-IMOMFO and the reason for the relationships is analyzed. The operation results show that the ecological demand and navigation demand have obvious contradictory relationships. |
| ArticleNumber | 124431 |
| Author | Yao, Liqiang Feng, Zhongkai Ouyang, Shuo Liu, Yongqi Zhang, Zhendong Qin, Hui Jiang, Zhiqiang |
| Author_xml | – sequence: 1 givenname: Zhendong surname: Zhang fullname: Zhang, Zhendong organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China – sequence: 2 givenname: Hui surname: Qin fullname: Qin, Hui email: hqin@hust.edu.cn organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China – sequence: 3 givenname: Liqiang surname: Yao fullname: Yao, Liqiang organization: Changjiang River Scientific Research Institute of Changjiang Water Resources Commission, Wuhan, Hubei, China – sequence: 4 givenname: Yongqi surname: Liu fullname: Liu, Yongqi organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China – sequence: 5 givenname: Zhiqiang surname: Jiang fullname: Jiang, Zhiqiang organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China – sequence: 6 givenname: Zhongkai surname: Feng fullname: Feng, Zhongkai organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China – sequence: 7 givenname: Shuo surname: Ouyang fullname: Ouyang, Shuo organization: Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan, Hubei, China |
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| Keywords | Improved Moth-flame optimization algorithm Ecology Multi-objective optimization Navigation Cascade reservoir operation R-domination |
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| Snippet | •A multi-objective model considering power generation, ecology and navigation is established.•A novel multi-objective evolutionary algorithm is proposed to... Traditional power generation operation of reservoir mainly considers the maximization of power generation and guarantees the stability of the power system.... |
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| SubjectTerms | algorithms Cascade reservoir operation Ecology flight hydrology Improved Moth-flame optimization algorithm moths Multi-objective optimization Navigation power generation R-domination |
| Title | Improved Multi-objective Moth-flame Optimization Algorithm based on R-domination for cascade reservoirs operation |
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