Maximizing firm wind connection to security constrained transmission networks

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Title: Maximizing firm wind connection to security constrained transmission networks
Authors: Burke, Daniel J.
O'Malley, Mark
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Date: May-2010
Abstract: Prudent use of existing transmission capacity could be achieved by an optimal allocation of wind capacity to distinct transmission nodes. The statistical interdependency of geographically separate wind sites and the partially-dispatchable nature of wind power require a collective analysis of all potential wind farms over an extended time-frame in any optimized transmission planning study. The methodology presented in this paper separates this large optimization problem into smaller subtasks, including a year-long sequential time series hourly integer unit commitment, a linear dc load-flow network model with hourly security constraints, and a linear programming optimization model to estimate the maximum firm wind energy penetration for a given network. A novel maximal vector based constraint redundancy analysis is employed to significantly reduce the linear programming optimization dimensionality. Firm wind capacity connections are facilitated in this paper—i.e., those to which wind curtailment to manage congestion is not applicable within a typical system "planning" timeframe analysis. Each bus is allocated firm capacity on the basis of maximizing the possible firm wind energy penetration in the transmission system as a whole, while preserving traditional network security standards.
Funding Details: Irish Research Council for Science, Engineering and Technology
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Power Systems
Volume: 25
Issue: 2
Start page: 749
End page: 759
Series/Report no.: Electricity Research Centre(ERC)
Copyright (published version): 2009 IEEE
Keywords: Computational geometryLinear programming redundancyPower transmissionWind energy
Subject LCSH: Electric power production--Linear programming
Electric power transmission--Planning
Wind power plants
DOI: 10.1109/TPWRS.2009.2033931
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Language: en
Status of Item: Peer reviewed
Appears in Collections:ERC Research Collection
Electrical and Electronic Engineering Research Collection

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