A hybrid of real coded genetic algorithm and artificial fish swarm algorithm for short-term optimal hydrothermal scheduling
•We present a SHS model to analyze the operation of hydrothermal power system.•Transmission losses, ramp rate limits and prohibited discharge zones are considered.•We propose a hybrid algorithm combining RCGA with AFSA.•We present the coarse and fine adjustment methods to deal with the constraints.•...
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| Published in | International journal of electrical power & energy systems Vol. 62; pp. 617 - 629 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Elsevier Ltd
01.11.2014
Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | •We present a SHS model to analyze the operation of hydrothermal power system.•Transmission losses, ramp rate limits and prohibited discharge zones are considered.•We propose a hybrid algorithm combining RCGA with AFSA.•We present the coarse and fine adjustment methods to deal with the constraints.•The results show that the proposed method can provide better solution.
The short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a series of hydraulic and electric system constraints. This paper presents a hybrid algorithm for solving SHS problem by combining real coded genetic algorithm and artificial fish swarm algorithm (RCGA–AFSA), which takes advantage of their complementary ability of global and local search for optimal solution. Real coded genetic algorithm (RCGA) is applied as global search, which can explore more promising solution spaces and give a good direction to the global optimal region. Artificial fish swarm algorithm (AFSA) is used as local search to obtain the final optimal solution for improving the exploitation capability of algorithm. The water transport delay between connected reservoirs is taken into account in this paper. Moreover, new coarse and fine adjustment methods without any penalty factors and extra parameters are proposed to deal with all equality and inequality constraints. To verify the feasibility and effectiveness of RCGA–AFSA, the proposed method is tested on two hydrothermal systems. Compared with other methods reported in the literature, the simulation results obtained by hybrid RCGA–AFSA are superior in fuel cost and computation time. |
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| AbstractList | •We present a SHS model to analyze the operation of hydrothermal power system.•Transmission losses, ramp rate limits and prohibited discharge zones are considered.•We propose a hybrid algorithm combining RCGA with AFSA.•We present the coarse and fine adjustment methods to deal with the constraints.•The results show that the proposed method can provide better solution.
The short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a series of hydraulic and electric system constraints. This paper presents a hybrid algorithm for solving SHS problem by combining real coded genetic algorithm and artificial fish swarm algorithm (RCGA–AFSA), which takes advantage of their complementary ability of global and local search for optimal solution. Real coded genetic algorithm (RCGA) is applied as global search, which can explore more promising solution spaces and give a good direction to the global optimal region. Artificial fish swarm algorithm (AFSA) is used as local search to obtain the final optimal solution for improving the exploitation capability of algorithm. The water transport delay between connected reservoirs is taken into account in this paper. Moreover, new coarse and fine adjustment methods without any penalty factors and extra parameters are proposed to deal with all equality and inequality constraints. To verify the feasibility and effectiveness of RCGA–AFSA, the proposed method is tested on two hydrothermal systems. Compared with other methods reported in the literature, the simulation results obtained by hybrid RCGA–AFSA are superior in fuel cost and computation time. The short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a series of hydraulic and electric system constraints. This paper presents a hybrid algorithm for solving SHS problem by combining real coded genetic algorithm and artificial fish swarm algorithm (RCGA-AFSA), which takes advantage of their complementary ability of global and local search for optimal solution. Real coded genetic algorithm (RCGA) is applied as global search, which can explore more promising solution spaces and give a good direction to the global optimal region. Artificial fish swarm algorithm (AFSA) is used as local search to obtain the final optimal solution for improving the exploitation capability of algorithm. The water transport delay between connected reservoirs is taken into account in this paper. Moreover, new coarse and fine adjustment methods without any penalty factors and extra parameters are proposed to deal with all equality and inequality constraints. To verify the feasibility and effectiveness of RCGA-AFSA, the proposed method is tested on two hydrothermal systems. Compared with other methods reported in the literature, the simulation results obtained by hybrid RCGA-AFSA are superior in fuel cost and computation time. |
| Author | Fang, Na Zhou, Jianzhong Zhang, Rui Liu, Yi Zhang, Yongchuan |
| Author_xml | – sequence: 1 givenname: Na surname: Fang fullname: Fang, Na organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China – sequence: 2 givenname: Jianzhong surname: Zhou fullname: Zhou, Jianzhong email: jz.zhou@mail.hust.edu.cn organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China – sequence: 3 givenname: Rui surname: Zhang fullname: Zhang, Rui organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China – sequence: 4 givenname: Yi surname: Liu fullname: Liu, Yi organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China – sequence: 5 givenname: Yongchuan surname: Zhang fullname: Zhang, Yongchuan organization: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, PR China |
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| Keywords | Constraints handling Artificial fish swarm algorithm Real coded genetic algorithm Short-term hydrothermal scheduling Short term Performance evaluation Costs Optimization method Scheduling Nonlinear problems Water flow Penalty function Computation time Genetic algorithm Optimal solution Inequality constraint Equality constraint System simulation Feasibility Delay time Optimal planning Effectiveness factor Comparative study |
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| Snippet | •We present a SHS model to analyze the operation of hydrothermal power system.•Transmission losses, ramp rate limits and prohibited discharge zones are... The short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a series of hydraulic and electric system constraints. This... |
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| SubjectTerms | Algorithms Applied sciences Artificial fish swarm algorithm Constraints handling Electrical engineering. Electrical power engineering Exact sciences and technology Fish Genetic algorithms Mathematical models Optimization Real coded genetic algorithm Scheduling Searching Self-propagating synthesis Short-term hydrothermal scheduling |
| Title | A hybrid of real coded genetic algorithm and artificial fish swarm algorithm for short-term optimal hydrothermal scheduling |
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