New formulations of the Optimal Power Flow (OPF) problem

Duration: 55 mins 40 secs

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Description:	Kirschen, D (Manchester) Tuesday 25 May 2010, 15:45-17:00

Created:

2010-05-28 12:39

Collection:

Stochastic Processes in Communication Sciences

Publisher:

Isaac Newton Institute

Kirschen, D

Language:

eng (English)

Credits:

Author:	Kirschen, D
Producer:	Steve Greenham


Abstract:	Transmission system operators are responsible for maintaining the security of the power system ("keeping the lights on") even when the system is affected by unpredictable but unavoidable contingencies such as the sudden loss of a transmission line or the sudden outage of a generating plant. To achieve this, they typically use a combination of corrective actions (e.g. redispacthing the generating units after a contingency has occurred) or preventive actions (i.e. keeping the system in a state such that it will not collapse if a contingency does occur - a "secure" state). This can be formulated as a very large non-linear optimisation problem because the state of a network with thousands of nodes and branches must be checked from thousands of credible contingencies. In recent years, this problem has become even more complex because of the added uncertainty introduced by the stochastic nature of wind generation. Operators would very much like to know what the worst pattern of credible uncertainty is and whether they have enough resources to cope with any contingency using corrective actions if this pattern of uncertainty does materialise.

Abstract:

Transmission system operators are responsible for maintaining the security of the power system ("keeping the lights on") even when the system is affected by unpredictable but unavoidable contingencies such as the sudden loss of a transmission line or the sudden outage of a generating plant. To achieve this, they typically use a combination of corrective actions (e.g. redispacthing the generating units after a contingency has occurred) or preventive actions (i.e. keeping the system in a state such that it will not collapse if a contingency does occur - a "secure" state). This can be formulated as a very large non-linear optimisation problem because the state of a network with thousands of nodes and branches must be checked from thousands of credible contingencies.
In recent years, this problem has become even more complex because of the added uncertainty introduced by the stochastic nature of wind generation. Operators would very much like to know what the worst pattern of credible uncertainty is and whether they have enough resources to cope with any contingency using corrective actions if this pattern of uncertainty does materialise.

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