A Heterogeneous Evolving Cuckoo Search Algorithm for Solving Large-Scale Combined Heat and Power Economic Dispatch Problems
Combined heat and power economic dispatch (CHPED) problem aims to optimally schedule the output of generating units with minimum fuel cost, which is a highly non-linear, non-convex and large-scale global optimization problem with many practical constraints. The complexity of the problem demands solu...
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          | Published in | IEEE access Vol. 7; pp. 111287 - 111301 | 
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| Main Authors | , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Piscataway
          IEEE
    
        2019
     The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  | 
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| Online Access | Get full text | 
| ISSN | 2169-3536 2169-3536  | 
| DOI | 10.1109/ACCESS.2019.2933980 | 
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| Abstract | Combined heat and power economic dispatch (CHPED) problem aims to optimally schedule the output of generating units with minimum fuel cost, which is a highly non-linear, non-convex and large-scale global optimization problem with many practical constraints. The complexity of the problem demands solution methods with powerful search ability, robustness, and computational efficiency. This paper proposes a heterogeneous evolving cuckoo search (HECS) algorithm with a novel constraint-handling mechanism to solve the large-scale CHPED problem considering valve-point effect. Based on the cuckoo search algorithm, we apply a comprehensive learning strategy to enhance the search ability in the high-dimensional environment, and a heterogeneous evolving strategy to improve the robustness of the algorithm. Moreover, we develop a novel constraint-handling mechanism that uses strict mathematical methods to repair unfeasible solutions and avoid redundant calculation. 5 tests are conducted on 24-unit, 48-unit, 84-unit, 96-unit, and 192-unit systems and the results are compared with the state-of-the-art algorithms published in the year 2015-2019. The comparisons show that the HECS could annually save millions of dollars in some large-scale systems, which verify its effectiveness. | 
    
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| AbstractList | Combined heat and power economic dispatch (CHPED) problem aims to optimally schedule the output of generating units with minimum fuel cost, which is a highly non-linear, non-convex and large-scale global optimization problem with many practical constraints. The complexity of the problem demands solution methods with powerful search ability, robustness, and computational efficiency. This paper proposes a heterogeneous evolving cuckoo search (HECS) algorithm with a novel constraint-handling mechanism to solve the large-scale CHPED problem considering valve-point effect. Based on the cuckoo search algorithm, we apply a comprehensive learning strategy to enhance the search ability in the high-dimensional environment, and a heterogeneous evolving strategy to improve the robustness of the algorithm. Moreover, we develop a novel constraint-handling mechanism that uses strict mathematical methods to repair unfeasible solutions and avoid redundant calculation. 5 tests are conducted on 24-unit, 48-unit, 84-unit, 96-unit, and 192-unit systems and the results are compared with the state-of-the-art algorithms published in the year 2015-2019. The comparisons show that the HECS could annually save millions of dollars in some large-scale systems, which verify its effectiveness. | 
    
| Author | Gao, Zhengzhong Huang, Zhenyu Duan, Hua Qi, Liang  | 
    
| Author_xml | – sequence: 1 givenname: Zhenyu orcidid: 0000-0001-5072-2050 surname: Huang fullname: Huang, Zhenyu organization: College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China – sequence: 2 givenname: Zhengzhong surname: Gao fullname: Gao, Zhengzhong email: zzgao@sdust.edu.cn organization: College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China – sequence: 3 givenname: Liang orcidid: 0000-0002-0762-5607 surname: Qi fullname: Qi, Liang organization: Department of Intelligent Science and Technology, Shandong University of Science and Technology, Qingdao, China – sequence: 4 givenname: Hua surname: Duan fullname: Duan, Hua email: hduan@sdust.edu.cn organization: College of Mathematics and System Science, Shandong University of Science and Technology, Qingdao, China  | 
    
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| SubjectTerms | Algorithms Cogeneration Combined heat and power economic dispatch constraint-handling mechanism cuckoo search Evolution Global optimization large-scale global optimization Machine learning Optimization Power dispatch Robustness Robustness (mathematics) Schedules Search algorithms Search problems STEM System effectiveness valve-point effect  | 
    
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| Title | A Heterogeneous Evolving Cuckoo Search Algorithm for Solving Large-Scale Combined Heat and Power Economic Dispatch Problems | 
    
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