Title: Wake steering optimization under uncertainty

Abstract

Turbines in wind power plants experience significant power losses when wakes from upstream turbines affect the energy production of downstream turbines. A promising plant-level control strategy to reduce these losses is wake steering, where upstream turbines are yawed to direct wakes away from downstream turbines. However, there are significant uncertainties in many aspects of the wake steering problem. For example, infield sensors do not give perfect information, and inflow to the plant is complex and difficult to forecast with available information, even over short time periods. Here, we formulate and solve an optimization under uncertainty (OUU) problem for determining optimal plant-level wake steering strategies in the presence of independent uncertainties in the direction, speed, turbulence intensity, and shear of the incoming wind, as well as in turbine yaw positions. The OUU wake steering strategy is first examined for a two-turbine test case to explore the impacts of different types of inflow uncertainties, and it is then demonstrated for a more realistic 11-turbine wind power plant. Of the sources of uncertainty considered, we find that wake steering strategies are most sensitive to uncertainties in the wind speed and direction. When maximizing expected power production, the OUU strategy also tends to favormore » smaller yaw angles, which have been shown in previous work to reduce turbine loading. Ultimately, the plant-level wake steering strategy formulated using an OUU approach yields 0.48?% more expected annual energy production for the 11-turbine wind plant than a strategy that neglects uncertainty when considering stochastic inputs. Thus, not only does the present OUU strategy produce more power in realistic conditions, but it also reduces risk by prescribing strategies that call for less extreme yaw angles.« less

Authors:

Quick, Julian ^[1]; King, Jennifer  ^[2];

• Search DOE PAGES for author "King, Jennifer"
• Search DOE PAGES for ORCID "0000-0001-6219-0098"

King, Ryan N. ^[2]; Hamlington, Peter E. ^[3]; Dykes, Katherine  ^[2]

• Search DOE PAGES for author "Dykes, Katherine"
• Search DOE PAGES for ORCID "0000-0002-5734-3122"

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+ Show Author Affiliations

1. Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
3. Univ. of Colorado, Boulder, CO (United States)

Publication Date:

Mon Mar 30 00:00:00 EDT 2020

Research Org.:

National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Org.:

USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office

OSTI Identifier:

1659960

Report Number(s):

NREL/JA-2C00-77181
Journal ID: ISSN 2366-7443; MainId:26127;UUID:b6ef6bef-4f38-4cef-9e45-6fa074687cf4;MainAdminID:13695

Grant/Contract Number:  

AC36-08GO28308

Resource Type:

Accepted Manuscript

Journal Name:

Wind Energy Science

Additional Journal Information:

Journal Volume: 5; Journal Issue: 1; Journal ID: ISSN 2366-7443

Publisher:

European Wind Energy Association - Copernicus

Country of Publication:

United States

Language:

English

Subject:

17 WIND ENERGY; optimization under uncertainty; wake steering