Abstract

The depletion of fossil fuel resources as well as commitments to lower the global emission of green house gases are driving many countries to make substantial investments in renewable energy resources, especially wind energy. In this regard, the United Kingdom has launched many off-shore and on-shore wind power projects which are planned to supply around 15% of energy demand by 2020. The network expansion required to accommodate this level of wind power is prohibitively expensive and time-consuming. Instead, some “Smart Grid” ideas can be used to enhance the utilization of network assets so that the transmission network expansion can be deferred or even avoided. Among these ideas, dynamic thermal rating is being investigated by National Grid for possible implementation in the Humber Estuary region where a high penetration of wind power is scheduled. In this paper, a probabilistic approach is introduced to answer two questions: (i) which transmission lines in Humber Estuary need to be considered in dynamic thermal rating scheme and (ii) how much benefit can be achieved by online monitoring of network thermal ratings? To answer these questions, probabilistic models for seasonal off-shore wind power as well as seasonal dynamic thermal ratings of overhead lines are developed, taking into account past meteorological data.

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