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Spatio-temporal correlations of available wind power and impact on transmission power flows

Bell, K.R.W. and Hill, D.C. and McMillan, D. and Li, F. and Dunn, R.W. and Infield, D.G. and Ault, G.W. Financial support for the work reported in section 4 was received from the UK government’s Dept of Energy and Climate Change. (Funder) (2010) Spatio-temporal correlations of available wind power and impact on transmission power flows. In: 43rd CIGRE session, 2010-08-08.

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This paper presents a description of a number of points of debate concerning the possible impact of future wind power development on power system planning and operation. It is noted that firm conclusions cannot be reached without adequate modelling of available power. Whilst this would normally require many years of experience of wind farm operation across a wide geographical area, in Britain such data are currently unavailable. However, more extensive coverage via national meteorological centre data may be available to facilitate a synthesis of future patterns of available wind power. These can be used by a transmission planner to assess the distribution of possible flows across main transmission boundaries. To be useful, the approach must respect the correlations of available wind power at different locations on the system. Furthermore, trends in wind speed through a day and through a year must be reliably reproduced captured so that the relationship to annual and diurnal load variations can subsequently be studied. A wind synthesis methodology is described. By being based on many years of wind speed data it permits the estimation of long-term risks associated with more extreme wind conditions. After dealing with gaps in the original wind speed dataset, a vector autoregression (VAR) approach is used to model wind speeds. Wind speeds generated by the model are converted to those that may be observed at 'typical' wind farm locations at 10m above ground level for different terrain types in different zones and then converted to hub height. The 'per unit' available wind power is then calculated by use of a wind speed to power curve. After having specified the total wind generation capacity in each terrain in each zone for the scenario they wish to study, the user of the tool is then able to calculate the total available power. When combined with scenarios describing oad demand and the availability and dispatch of conventional generation, future capacity margins and power flows can be studied, e.g. for identification of future system reinforcement requirements. An extension of the approach is presented that permits study of available power and power flows through a year of operation. This also uses vector autoregression (VAR) to model wind speeds but is applied after a careful detrending process to allow diurnal and seasonal effects to be correctly treated. Finally, future developments of the approach are outlined and it is suggested that the same approach may be useful not only in power system planning but also in support of power system operation.