Monitoring offshore wind farm power performance with SCADA data and an advanced wake model

Mittelmeier, Niko; Blodau, Tomas; Kühn, Martin

doi:10.5194/wes-2-175-2017

Articles | Volume 2, issue 1

https://doi.org/10.5194/wes-2-175-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/wes-2-175-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 2, issue 1

Research article

|

28 Mar 2017

Research article |

| 28 Mar 2017

Monitoring offshore wind farm power performance with SCADA data and an advanced wake model

Niko Mittelmeier, Tomas Blodau, and Martin Kühn

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Total article views: 3,898 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
1,939	1,795	164	3,898	199	208

HTML: 1,939
PDF: 1,795
XML: 164
Total: 3,898
BibTeX: 199
EndNote: 208

Views and downloads (calculated since 17 May 2016)

Month	HTML	PDF	XML	Total
May 2016	25	13	1	39
Jun 2016	25	3	1	29
Jul 2016	18	5	2	25
Aug 2016	13	6	1	20
Sep 2016	10	15	0	25
Oct 2016	9	5	2	16
Nov 2016	5	8	0	13
Dec 2016	8	4	0	12
Jan 2017	7	6	1	14
Feb 2017	7	9	0	16
Mar 2017	66	39	3	108
Apr 2017	66	63	2	131
May 2017	39	52	1	92
Jun 2017	44	21	1	66
Jul 2017	17	21	0	38
Aug 2017	7	15	0	22
Sep 2017	15	16	1	32
Oct 2017	14	15	0	29
Nov 2017	9	16	1	26
Dec 2017	7	14	0	21
Jan 2018	9	10	0	19
Feb 2018	22	17	3	42
Mar 2018	10	25	2	37
Apr 2018	8	12	0	20
May 2018	11	10	1	22
Jun 2018	14	17	2	33
Jul 2018	9	12	3	24
Aug 2018	13	14	1	28
Sep 2018	9	14	0	23
Oct 2018	13	8	1	22
Nov 2018	12	9	2	23
Dec 2018	10	16	3	29
Jan 2019	13	20	0	33
Feb 2019	11	14	1	26
Mar 2019	14	18	0	32
Apr 2019	12	15	0	27
May 2019	6	8	0	14
Jun 2019	8	11	0	19
Jul 2019	5	13	1	19
Aug 2019	9	13	0	22
Sep 2019	7	13	0	20
Oct 2019	23	15	2	40
Nov 2019	12	12	0	24
Dec 2019	18	4	0	22
Jan 2020	32	6	2	40
Feb 2020	19	9	0	28
Mar 2020	18	12	1	31
Apr 2020	7	9	0	16
May 2020	7	14	0	21
Jun 2020	34	36	1	71
Jul 2020	62	100	40	202
Aug 2020	11	9	1	21
Sep 2020	11	13	0	24
Oct 2020	11	14	2	27
Nov 2020	3	7	0	10
Dec 2020	16	13	1	30
Jan 2021	25	18	0	43
Feb 2021	20	21	0	41
Mar 2021	18	13	0	31
Apr 2021	17	19	0	36
May 2021	19	20	1	40
Jun 2021	17	21	0	38
Jul 2021	15	11	1	27
Aug 2021	11	16	0	27
Sep 2021	10	15	0	25
Oct 2021	8	40	0	48
Nov 2021	10	32	1	43
Dec 2021	17	11	2	30
Jan 2022	9	17	1	27
Feb 2022	10	18	2	30
Mar 2022	8	12	0	20
Apr 2022	21	17	1	39
May 2022	13	11	1	25
Jun 2022	11	5	0	16
Jul 2022	19	8	0	27
Aug 2022	22	9	1	32
Sep 2022	11	5	0	16
Oct 2022	18	10	3	31
Nov 2022	15	16	0	31
Dec 2022	29	21	4	54
Jan 2023	16	15	0	31
Feb 2023	23	10	1	34
Mar 2023	25	13	4	42
Apr 2023	13	4	2	19
May 2023	21	16	2	39
Jun 2023	9	7	0	16
Jul 2023	12	10	2	24
Aug 2023	15	10	3	28
Sep 2023	12	12	2	26
Oct 2023	14	5	1	20
Nov 2023	5	3	0	8
Dec 2023	16	12	5	33
Jan 2024	13	15	0	28
Feb 2024	10	10	0	20
Mar 2024	7	28	0	35
Apr 2024	13	12	2	27
May 2024	14	8	5	27
Jun 2024	17	14	5	36
Jul 2024	22	16	3	41
Aug 2024	17	9	3	29
Sep 2024	12	14	2	28
Oct 2024	19	9	2	30
Nov 2024	7	9	1	17
Dec 2024	12	19	1	32
Jan 2025	12	13	0	25
Feb 2025	29	6	0	35
Mar 2025	15	15	1	31
Apr 2025	19	22	1	42
May 2025	22	11	1	34
Jun 2025	54	23	1	78
Jul 2025	23	19	0	42
Aug 2025	26	25	0	51
Sep 2025	44	30	6	80
Oct 2025	27	32	2	61
Nov 2025	31	25	1	57

Cumulative views and downloads (calculated since 17 May 2016)

Month	HTML	PDF	XML	Total
May 2016	25	13	1	39
Jun 2016	25	3	1	29
Jul 2016	18	5	2	25
Aug 2016	13	6	1	20
Sep 2016	10	15	0	25
Oct 2016	9	5	2	16
Nov 2016	5	8	0	13
Dec 2016	8	4	0	12
Jan 2017	7	6	1	14
Feb 2017	7	9	0	16
Mar 2017	66	39	3	108
Apr 2017	66	63	2	131
May 2017	39	52	1	92
Jun 2017	44	21	1	66
Jul 2017	17	21	0	38
Aug 2017	7	15	0	22
Sep 2017	15	16	1	32
Oct 2017	14	15	0	29
Nov 2017	9	16	1	26
Dec 2017	7	14	0	21
Jan 2018	9	10	0	19
Feb 2018	22	17	3	42
Mar 2018	10	25	2	37
Apr 2018	8	12	0	20
May 2018	11	10	1	22
Jun 2018	14	17	2	33
Jul 2018	9	12	3	24
Aug 2018	13	14	1	28
Sep 2018	9	14	0	23
Oct 2018	13	8	1	22
Nov 2018	12	9	2	23
Dec 2018	10	16	3	29
Jan 2019	13	20	0	33
Feb 2019	11	14	1	26
Mar 2019	14	18	0	32
Apr 2019	12	15	0	27
May 2019	6	8	0	14
Jun 2019	8	11	0	19
Jul 2019	5	13	1	19
Aug 2019	9	13	0	22
Sep 2019	7	13	0	20
Oct 2019	23	15	2	40
Nov 2019	12	12	0	24
Dec 2019	18	4	0	22
Jan 2020	32	6	2	40
Feb 2020	19	9	0	28
Mar 2020	18	12	1	31
Apr 2020	7	9	0	16
May 2020	7	14	0	21
Jun 2020	34	36	1	71
Jul 2020	62	100	40	202
Aug 2020	11	9	1	21
Sep 2020	11	13	0	24
Oct 2020	11	14	2	27
Nov 2020	3	7	0	10
Dec 2020	16	13	1	30
Jan 2021	25	18	0	43
Feb 2021	20	21	0	41
Mar 2021	18	13	0	31
Apr 2021	17	19	0	36
May 2021	19	20	1	40
Jun 2021	17	21	0	38
Jul 2021	15	11	1	27
Aug 2021	11	16	0	27
Sep 2021	10	15	0	25
Oct 2021	8	40	0	48
Nov 2021	10	32	1	43
Dec 2021	17	11	2	30
Jan 2022	9	17	1	27
Feb 2022	10	18	2	30
Mar 2022	8	12	0	20
Apr 2022	21	17	1	39
May 2022	13	11	1	25
Jun 2022	11	5	0	16
Jul 2022	19	8	0	27
Aug 2022	22	9	1	32
Sep 2022	11	5	0	16
Oct 2022	18	10	3	31
Nov 2022	15	16	0	31
Dec 2022	29	21	4	54
Jan 2023	16	15	0	31
Feb 2023	23	10	1	34
Mar 2023	25	13	4	42
Apr 2023	13	4	2	19
May 2023	21	16	2	39
Jun 2023	9	7	0	16
Jul 2023	12	10	2	24
Aug 2023	15	10	3	28
Sep 2023	12	12	2	26
Oct 2023	14	5	1	20
Nov 2023	5	3	0	8
Dec 2023	16	12	5	33
Jan 2024	13	15	0	28
Feb 2024	10	10	0	20
Mar 2024	7	28	0	35
Apr 2024	13	12	2	27
May 2024	14	8	5	27
Jun 2024	17	14	5	36
Jul 2024	22	16	3	41
Aug 2024	17	9	3	29
Sep 2024	12	14	2	28
Oct 2024	19	9	2	30
Nov 2024	7	9	1	17
Dec 2024	12	19	1	32
Jan 2025	12	13	0	25
Feb 2025	29	6	0	35
Mar 2025	15	15	1	31
Apr 2025	19	22	1	42
May 2025	22	11	1	34
Jun 2025	54	23	1	78
Jul 2025	23	19	0	42
Aug 2025	26	25	0	51
Sep 2025	44	30	6	80
Oct 2025	27	32	2	61
Nov 2025	31	25	1	57

Latest update: 21 Nov 2025

Short summary

Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method presented estimates the environmental conditions from turbine states and uses pre-calculated power lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. A demonstration of the method's ability to detect underperformance is given.