Abstract
A wind farm optimization framework is presented in detail and demonstrated on two test cases: 1) Middelgrunden and 2) Stags Holt/Coldham. A detailed flow model describing the instationary flow
within a wind farm is used together with an aeroelastic model to determine production and fatigue loading of wind farm wind turbines. Based on generic load cases, the wind farm production and fatigue evaluations are subsequently condensed in a large pre-calculated database for rapid calculation of lifetime equivalent loads and energy production in the optimization loop.. The objective function defining the optimization problem includes elements as energy production, turbine degradation, operation and maintenance costs, electrical grid costs and foundation costs. The objective function is optimized using a dedicated multi fidelity approach with the locations of individual turbines in the wind farm spanning the design space. . The results are over all satisfying and are giving some interesting insights on the pros and cons of the design choices. They show in particular that the inclusion of the fatigue loads costs give rise to some additional details in comparison with pure power based optimization. The Middelgrunden test case resulted in an improvement of the financial balance of 2.1 M€ originating from a very large increase in the energy production value of 9.3 M€ mainly counterbalanced by increased
electrical grid costs. The Stags Holt/Coldham test case resulted in an improvement of the financial balance of 3.1 M€.
within a wind farm is used together with an aeroelastic model to determine production and fatigue loading of wind farm wind turbines. Based on generic load cases, the wind farm production and fatigue evaluations are subsequently condensed in a large pre-calculated database for rapid calculation of lifetime equivalent loads and energy production in the optimization loop.. The objective function defining the optimization problem includes elements as energy production, turbine degradation, operation and maintenance costs, electrical grid costs and foundation costs. The objective function is optimized using a dedicated multi fidelity approach with the locations of individual turbines in the wind farm spanning the design space. . The results are over all satisfying and are giving some interesting insights on the pros and cons of the design choices. They show in particular that the inclusion of the fatigue loads costs give rise to some additional details in comparison with pure power based optimization. The Middelgrunden test case resulted in an improvement of the financial balance of 2.1 M€ originating from a very large increase in the energy production value of 9.3 M€ mainly counterbalanced by increased
electrical grid costs. The Stags Holt/Coldham test case resulted in an improvement of the financial balance of 3.1 M€.
| Original language | English |
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| Publisher | Risø National Laboratory for Sustainable Energy, Technical University of Denmark |
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| Number of pages | 94 |
| ISBN (Electronic) | 978-87-550-3884-4 |
| Publication status | Published - 2011 |
| Series | Denmark. Forskningscenter Risoe. Risoe-R |
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| Number | 1768(EN) |
| ISSN | 0106-2840 |
Keywords
- Risø-R-1768
- Risø-R-1768(EN)