The ε constrained differential evolution approach for optimal operational planning of energy plants
This paper introduces optimal operational planning of energy plants via the ε constrained differential evolution. In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. T...
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| creator | Suzuki, Ryohei Kawai, Fukiko Kitagawa, Shinji Matsui, Tetsuro Matsumoto, Kouji Donghui Xiang Fukuyama, Yoshikazu |
| description | This paper introduces optimal operational planning of energy plants via the ε constrained differential evolution. In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. The problem can be formulated as a large-scale mixed-integer nonlinear problem (MINLP). Metaheuristics (MHs) is one of the solutions for MINLP. If the formulated MINLP has various equality and inequality constraints, it remains difficult to solve it without parameters tuning. In this paper, to overcome the difficulty, we propose an improved differential evolution approach using the ε constrained method for MINLP. Results show the effectiveness of the proposed method compared with conventional methods. |
| doi_str_mv | 10.1109/CEC.2010.5586322 |
| format | Conference Proceeding |
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In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. The problem can be formulated as a large-scale mixed-integer nonlinear problem (MINLP). Metaheuristics (MHs) is one of the solutions for MINLP. If the formulated MINLP has various equality and inequality constraints, it remains difficult to solve it without parameters tuning. In this paper, to overcome the difficulty, we propose an improved differential evolution approach using the ε constrained method for MINLP. 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In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. The problem can be formulated as a large-scale mixed-integer nonlinear problem (MINLP). Metaheuristics (MHs) is one of the solutions for MINLP. If the formulated MINLP has various equality and inequality constraints, it remains difficult to solve it without parameters tuning. In this paper, to overcome the difficulty, we propose an improved differential evolution approach using the ε constrained method for MINLP. Results show the effectiveness of the proposed method compared with conventional methods.</abstract><pub>IEEE</pub><doi>10.1109/CEC.2010.5586322</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1089-778X |
| ispartof | IEEE Congress on Evolutionary Computation, 2010, p.1-6 |
| issn | 1089-778X 1941-0026 |
| language | eng |
| recordid | cdi_ieee_primary_5586322 |
| source | IEEE Xplore |
| subjects | Heat engines Planning Refrigerators Resistance heating Search problems Turbines |
| title | The ε constrained differential evolution approach for optimal operational planning of energy plants |
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