The use of active thermal energy storage can provide energy savings, cost reduction and CO2 mitigation by reducing energy demand for heating and cooling, allowing the use of peak load shifting strategies and enhancing the introduction of renewable energies in the sector. The high investment cost of these systems makes mandatory an appropriate control in order to maximize the energy benefits during its operation. Within this context artificial intelligence techniques have been successfully used to control active thermal energy storage units. This paper uses an experimentally validated numerical tool to study the effect of different control strategies on the performance of one TES system applied to the building sector, a ventilated facade with PCM which uses free cooling. Three different strategies were designed to control the ventilated facade based on cost savings, energy reduction and CO2 mitigation, under different climatic conditions. Results show robust benefits in the three tested control strategies, achieving average savings in comparison to a manual operation of the system of 4.3%, 7.8%, and 16.7%. Moreover, the paper shows that when the control strategy is focused on optimizing cost, the other two benefits claimed by TES systems (energy and CO2 mitigation) are significantly reduced. The work is partially funded by the Spanish Government (ENE2015-64117-C5-1-R (MINECO/FEDER), ENE2015-64117-C5-3-R (MINECO/FEDER), TIN2015-71799-C2-2-P and ULLE10-4E-1305). The authors would like to thank the Catalan Government for the quality accreditation given to their research group (2014 SGR 123) and the city hall of Puigverd de Lleida. This project has received funding from the European Commission Seventh Framework Programme (FP/2007-2013) under Grant agreement N°PIRSES-GA-2013-610692 (INNOSTORAGE) and from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 657466 (INPATH-TES), and the fund received by the Royal Society of New Zealand. Alvaro de Gracia would like to thank Ministerio de Economia y Competitividad de España for Grant Juan de la Cierva, FJCI-2014-19940.