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The aggregate demand flexibility of a set of thermostatically controlledresidential loads (TCLs) can be represented by a virtual battery (VB) in orderto manage their participation in the electricity markets. For this purpose, itis necessary to know in advance and with a high level of reliability themaximum power that can be supplied by the aggregation of TCLs. A probabilityfunction of the power that can be supplied by a VB is introduced. Thisprobability function is used to predict the demand flexibility using a newexperimental probabilistic method based on a combination of Monte Carlosimulation and extremum search by bisection algorithm (MC&ESB). As a result,the maximum flexibility power that a VB can provide with a certain guaranteedprobability is obtained. The performance and validity of the proposed methodare demonstrated in three different case studies where a VB bids its aggregatepower in the Spanish electricity balancing markets (SEBM).

Aggregated demand flexibility prediction of residential thermostatically controlled loads and participation in electricity balance markets