  The aggregate demand flexibility of a set of thermostatically controlled
residential loads (TCLs) can be represented by a virtual battery (VB) in order
to manage their participation in the electricity markets. For this purpose, it
is necessary to know in advance and with a high level of reliability the
maximum power that can be supplied by the aggregation of TCLs. A probability
function of the power that can be supplied by a VB is introduced. This
probability function is used to predict the demand flexibility using a new
experimental probabilistic method based on a combination of Monte Carlo
simulation and extremum search by bisection algorithm (MC&ESB). As a result,
the maximum flexibility power that a VB can provide with a certain guaranteed
probability is obtained. The performance and validity of the proposed method
are demonstrated in three different case studies where a VB bids its aggregate
power in the Spanish electricity balancing markets (SEBM).
