Operations Requirements of Utilities with Wind Power Generation

Chan, Steve; Powell, David C.; Yoshimura, Motoki; Curtice, D.

doi:10.1109/mper.1983.5519273

Cited by 14 publications

(17 citation statements)

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“…A joint research effort by Dr. Sherman Chan and the author aimed at quantifying in a probabilistic framework the load following, operating reserve and unloadable generation requirements for a utility with wind turbine power generation was reported in an EPRI report by and in a conference paper by Chan, Powell et al (1983). The present report considers in greater depth important meteorological ideas found in these reports.…”

Section: Discussionmentioning

confidence: 88%

Meteorological analysis for clusters of wind turbines

Powell¹

1984

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This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.

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Section: Discussionmentioning

confidence: 88%

Meteorological analysis for clusters of wind turbines

Powell¹

1984

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“…In this case, the power output of a wind farm for a specific state characterized can be obtained by summing up power output of all WTGs corresponding to the state (7) where is the power output of WTG for the state . For a wind farm at bus which consists of WTGs, the corresponding UGF of the can be defined as the following polynomial: (8) where is the probability for the state and is the number of wind speed states of the wind farm at bus .…”

Section: B Reliability Model Of a Wind Farmmentioning

confidence: 99%

Long-Term Reserve Expansion of Power Systems With High Wind Power Penetration Using Universal Generating Function Methods

Ding

Wang

Goel

et al. 2011

IEEE Trans. Power Syst.

133

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In a power system with high wind power penetration, reliability-based reserve expansion is a major problem of system planning and operation due to the uncertainty and fast fluctuation of wind speeds. This paper studied the impact of high wind power penetration on the system reserve and reliability from long-term planning point of view utilizing universal generating function (UGF) methods. The reliability models of wind farms and conventional generators are represented as the corresponding UGFs, and the special operators for these UGFs are defined to evaluate the customer and the system reliabilities. The effect of transmission network on customer reliabilities is also considered in the system UGF. The power output models of wind turbine generators in a wind farm considering wind speed correlation and un-correlation are developed, respectively. A reliability-based reserve expansion method is proposed to determine the conventional reserve required for power systems with high wind power penetration. The IEEE-RTS has been modified to illustrate the applications of the proposed method.

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“…As a result, the obtained predictions, for a future time horizon of a few minutes up to one hour ahead, were close to the persistent values; this implies that practically, there was no valuable change with regard to the most recent values. To this end, research activity was directed to spatial correlation studies of wind signals, not always leading to satisfactory models [10,30,31]. For distances of 20-100 km a significant correlation of the hourly or daily average wind speeds has been recognized.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, a decrease of the correlation factor is noticed when the wind direction axis differs considerably from the distance vector connecting the measurement sites [28]. In [10], the spatial correlation of wind turbulence is considered for distances of 700 m to 15 km and for time scales of 4, 10 and 30 min. It is concluded that the correlation coefficients strongly depend on the direction of the wind, terrain roughness and height above the ground.…”

Section: Introductionmentioning

confidence: 99%