Abstract:
In this research, the peak load diversity modelling of the Nigeria’s transmission grid
which contribute to effective and optimal expansion in grid capacity and reduction in
investment costs was considered and an algorithmic model for predicting delivery point
load on addition of new sub-transmission lines for optimal load design was developed.
Using diversity factor as a metric, the load diversity ( 𝛼𝑡) of the transmission grid was
obtained from the historical data. Optimal diversity (𝛼𝑜𝑝𝑡) was determined for each bus
by predicting the 330/132 kV delivery point load for the next 25 year based on historical
data from 2008 to 2014 using regression analysis. This was done by taking into
consideration the coefficient of correlation and least square error for the future diversity.
The obtained diversity factor was analyzed and modelled using frequency distribution,
relative frequency distribution and mean statistics function in EXCEL worksheet to
obtain most frequent and mean value for the transmission grid. An algorithmic model
based on obtained optimal diversity (𝛼𝑜𝑝𝑡) which takes into consideration the relative
error for the predicted load at 330 kV Bus and 132 kV was developed for predicting
delivery point load (𝑃𝐴) on addition of new sub-transmissions lines. The result presented the modelled mean load diversity (𝛼0) for each bus comprises of Shirorro 330 kV at 3.28, Jebba T.S 330 kV at 8.5, Mando T.S 330 kV at 1.33, Kumbotso 330 kV at 1.40,
Jos at 1.16, Gombe 330 kV at 1.83, Akangba 330 kV at 3.0, Aja 330 kV at 1.33, Ikeja
West 330 kV at 1.21, Osogbo 330 kV at 1.33, Ayede 330 kV at 1.41, Benin 330 kV at
1.49, New Haven 330 kV at 1.98, Onitsha330 kV at 1.11, Alaoji 330 kV at 1.32 and
Afam 330 kV at 2.99. The modelled diversity factor is recommended for use on addition
of new sub-transmission lines in Nigeria’s Transmission grid expansion planning.
