Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling
Culture belief is integrated into multi-objective differential evolution. Chaotic sequence is imported to improve evolutionary population diversity. The priority of convergence rate is proved in solving hydrothermal problem. The results show the quality and potential of proposed algorithm. A culture...
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| Published in: | Energy conversion and management Vol. 65; pp. 173 - 184 |
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01.01.2013
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| Abstract | Culture belief is integrated into multi-objective differential evolution. Chaotic sequence is imported to improve evolutionary population diversity. The priority of convergence rate is proved in solving hydrothermal problem. The results show the quality and potential of proposed algorithm.
A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE. |
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| AbstractList | Culture belief is integrated into multi-objective differential evolution. Chaotic sequence is imported to improve evolutionary population diversity. The priority of convergence rate is proved in solving hydrothermal problem. The results show the quality and potential of proposed algorithm.
A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE. A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE. |
| Author | Zhang, Huifeng Wang, Yongqiang Zhou, Jianzhong Lu, Youlin Zhang, Yongchuan |
| Author_xml | – sequence: 1 givenname: Huifeng surname: Zhang fullname: Zhang, Huifeng – sequence: 2 givenname: Jianzhong surname: Zhou fullname: Zhou, Jianzhong email: jz.zhou@hust.edu.cn – sequence: 3 givenname: Yongchuan surname: Zhang fullname: Zhang, Yongchuan – sequence: 4 givenname: Youlin surname: Lu fullname: Lu, Youlin – sequence: 5 givenname: Yongqiang surname: Wang fullname: Wang, Yongqiang |
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| Keywords | Short term hydrothermal Communication protocol Local optima Premature convergence Culture belief Economic emission Chaotic factor Population-based evolutionary model |
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| Snippet | Culture belief is integrated into multi-objective differential evolution. Chaotic sequence is imported to improve evolutionary population diversity. The... A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic... |
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| SubjectTerms | algorithms Applied sciences Chaotic factor Communication protocol Culture belief Economic emission Energy energy costs Exact sciences and technology Local optima nonlinear models Population-based evolutionary model Premature convergence problem solving Short term hydrothermal |
| Title | Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling |
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