| Description |
1 online resource (32 pages) : color illustrations. |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
NREL/PR ; 5000-73352 |
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NREL/PR ; 5000-73352.
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| Note |
"December 31, 2018." |
| Funding |
National Renewable Energy Laboratory DE-AC36-08GO28308 |
| Note |
Description based on online resource; title from PDF title page (NREL, viewed on June 29, 2021). |
| Summary |
Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. To enable cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving these cooperative wind farms is to develop algorithms that provide necessary information to ensure reliable and efficient operation of turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This presentation demonstrates a framework for implementing a cooperative wind. Farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more reliable estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbines spends yawing due to a more reliable input to the yaw controller, and increase resiliency to faulty wind-vane measurements. The concept was evaluated on data provided by WindESCo and was evaluated across several other averaging techniques to demonstrate the resiliency of the proposed consensus method. |
| Subject |
Winds -- United States.
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Vents -- États-Unis.
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Winds. (OCoLC)fst01175820
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United States. (OCoLC)fst01204155 https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq
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| Indexed Term |
consensus control |
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increased resiliency |
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SCADA |
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supervisory control and data acquisition |
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wind farm control |
| Added Author |
National Renewable Energy Laboratory (U.S.), issuing body.
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| Standard No. |
1501672 OSTI ID |
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0000-0001-6219-0098 |
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0000-0002-2658-5559 |
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0000-0001-8249-2544 |
| Gpo Item No. |
0430-P-09 (online) |
| Sudoc No. |
E 9.22:NREL/PR-5000-73352 |
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