Estimation of Joint Distribution of Demand and Available Renewables for Generation Adequacy Assessment

In recent years there has been a resurgence of interest in
generation adequacy risk assessment, due to the need to include
variable generation renewables within such calculations. This paper
will describe new statistical approaches to estimating the joint
distribution of demand and available VG capacity; this is required
for the LOLE calculations used in many statutory adequacy studies,
for example those of GB and PJM.

The most popular estimation technique in the VG-integration
literature is `hindcast', in which the historic joint distribution
of demand and available VG is used as a predictive
distribution. Through the use of bootstrap statistical analysis,
this paper will show that due to extreme sparsity of data on times
of high demand and low VG, hindcast results can suffer from sampling
uncertainty to the extent that they have little practical meaning.
An alternative estimation approach, in which a marginal distribution
of available VG is rescaled according to demand level, is thus
proposed. This reduces sampling uncertainty at the expense of the
additional model structure assumption, and further provides a means
of assessing the sensitivity of model outputs to the VG-demand
relationship by varying the function of demand by which the marginal
VG distribution is rescaled.