Abstract
One of the factors hindering the large scale integration of wind power is the post contingency congestion of a network due to limited availability of network capacity and auxiliary constraints. Under such conditions, the network operators can potentially request a curtailment of wind farm output if the remedial strategies fail. The paper investigates this problem in detail and proposes a mathematical framework to capture the post contingency spare capacity of network assets that is required to limit the wind curtailment. The proposed approach incorporates stochastic variation in asset thermal rating; models network congestion, and quantifies the risk of congestion using an extended version of conic-quadratic programming based optimization. The uniqueness of the proposed mathematical model is that it converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation penalty. The results suggest that the wind utilization can be maximized if the networks are operated 30-50% less than the nominal rating of the assets.
Original language | English |
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Title of host publication | 2014 Australasian Universities Power Engineering Conference, AUPEC 2014 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISBN (Print) | 9780646923758 |
DOIs | |
Publication status | Published - 24 Nov 2014 |
Event | 24th Australasian Universities Power Engineering Conference, AUPEC 2014 - Perth, Australia Duration: 28 Sept 2014 → 1 Oct 2014 |
Conference
Conference | 24th Australasian Universities Power Engineering Conference, AUPEC 2014 |
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Country/Territory | Australia |
City | Perth |
Period | 28/09/14 → 1/10/14 |
Keywords
- dynamic line ratings
- risk of congestion
- Wind power generation
ASJC Scopus subject areas
- Energy Engineering and Power Technology