Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming
This paper presents the application of MINLP (mixed-integer nonlinear programming) approach for scheduling of a CHP (combined heat and power) plant in the day-ahead wholesale energy markets. This work employs first principles models to describe the nonlinear dynamics of a CHP plant and its individua...
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| Published in: | Energy (Oxford) Vol. 77; pp. 675 - 690 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.12.2014
Elsevier |
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| ISSN: | 0360-5442 |
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| Abstract | This paper presents the application of MINLP (mixed-integer nonlinear programming) approach for scheduling of a CHP (combined heat and power) plant in the day-ahead wholesale energy markets. This work employs first principles models to describe the nonlinear dynamics of a CHP plant and its individual components. The MINLP framework includes practical constraints such as minimum/maximum power output and steam flow restrictions, minimum up/down times, start-up and shut-down procedures, and fuel limits. Special care is given to the explicit modeling of the unit start-up types (hot, warm, and cold), which depend on the component's prior reservation time, resulting in the differences in the time-dependent start-up costs of generating units. The model also accounts for the different operating modes (synchronization, soak, dispatch, and desynchronization) during start-up and shut-down of each unit. We provide case studies involving the Hal C. Weaver power plant complex at the University of Texas at Austin to demonstrate the effectiveness of the proposed methodology. The results show that the optimized operating strategies can yield substantial net incomes from electricity sales.
•Optimal scheduling of a CHP (combined heat and power) plant in the wholesale energy markets is proposed.•A mixed-integer nonlinear programming model is built to optimize power production.•Power production is maximized during on-peak hours due to high electricity prices.•The maximum profit is realized by committing more efficient generating units.•Less efficient generating units can be brought on-line due to operating constraints. |
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| AbstractList | This paper presents the application of MINLP (mixed-integer nonlinear programming) approach for scheduling of a CHP (combined heat and power) plant in the day-ahead wholesale energy markets. This work employs first principles models to describe the nonlinear dynamics of a CHP plant and its individual components. The MINLP framework includes practical constraints such as minimum/maximum power output and steam flow restrictions, minimum up/down times, start-up and shut-down procedures, and fuel limits. Special care is given to the explicit modeling of the unit start-up types (hot, warm, and cold), which depend on the component's prior reservation time, resulting in the differences in the time-dependent start-up costs of generating units. The model also accounts for the different operating modes (synchronization, soak, dispatch, and desynchronization) during start-up and shut-down of each unit. We provide case studies involving the Hal C. Weaver power plant complex at the University of Texas at Austin to demonstrate the effectiveness of the proposed methodology. The results show that the optimized operating strategies can yield substantial net incomes from electricity sales.
•Optimal scheduling of a CHP (combined heat and power) plant in the wholesale energy markets is proposed.•A mixed-integer nonlinear programming model is built to optimize power production.•Power production is maximized during on-peak hours due to high electricity prices.•The maximum profit is realized by committing more efficient generating units.•Less efficient generating units can be brought on-line due to operating constraints. This paper presents the application of MINLP (mixed-integer nonlinear programming) approach for scheduling of a CHP (combined heat and power) plant in the day-ahead wholesale energy markets. This work employs first principles models to describe the nonlinear dynamics of a CHP plant and its individual components. The MINLP framework includes practical constraints such as minimum/maximum power output and steam flow restrictions, minimum up/down times, start-up and shut-down procedures, and fuel limits. Special care is given to the explicit modeling of the unit start-up types (hot, warm, and cold), which depend on the component's prior reservation time, resulting in the differences in the time-dependent start-up costs of generating units. The model also accounts for the different operating modes (synchronization, soak, dispatch, and desynchronization) during start-up and shut-down of each unit We provide case studies involving the Hal C. Weaver power plant complex at the University of Texas at Austin to demonstrate the effectiveness of the proposed methodology. The results show that the optimized operating strategies can yield substantial net incomes from electricity sales. |
| Author | Edgar, Thomas F. Kim, Jong Suk |
| Author_xml | – sequence: 1 givenname: Jong Suk orcidid: 0000-0001-6179-4420 surname: Kim fullname: Kim, Jong Suk email: jkim0916@gmail.com, since801@hotmail.com organization: McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 E Dean Keeton St. Stop C0400, Austin, TX 78712-1589, USA – sequence: 2 givenname: Thomas F. surname: Edgar fullname: Edgar, Thomas F. organization: McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 E Dean Keeton St. Stop C0400, Austin, TX 78712-1589, USA |
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| Keywords | Scheduling Economic dispatch Day-ahead wholesale energy market Mixed-integer nonlinear programming Combined heat and power Unit commitment Electric power plant Non linear programming |
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| SubjectTerms | Applied sciences case studies CHP cold Combined heat and power Day-ahead wholesale energy market Economic dispatch electricity Energy Exact sciences and technology fuels heat income Markets Mathematical models Maximum power Mixed-integer nonlinear programming Nonlinear programming Power plants sales Scheduling steam Texas Unit commitment |
| Title | Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming |
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