Due to the increase of renewable energy sources in the electricity grid, demand-side flexibility, lead by Demand Response (DR), is gaining momentum to counteract the uncertainties of the new electricity system and contribute to grid balancing. At the same time, consumers are becoming active participants by engaging in flexibility actions enabled by demand aggregators. This project aims to integrate a microgrid laboratory with an aggregation platform in order to set up and configure the necessary tools to operate the laboratory as a platform to test flexibility. This way, the potential flexibility services that consumers can provide to the grid has been analysed. With the use of virtual, real and emulated elements from the laboratory, a more realistic impact and value of DR programs can be quantified. Two types of consumers have been defined: a residential one (Scenario 1), with a Heating Ventilation and Air Conditioning (HVAC) unit and a prosumer (Scenario 2), owning a battery in a solar Photovoltaic (PV) selfconsumption system. For both scenarios, the effect of receiving flexibility activations from the aggregator has been analysed and compared with a base case in which no interaction with the aggregator occurs. In addition, OpenADR, a relevant protocol for DR has been implemented and tested in the laboratory (Scenario 3). The experimental work developed shows that demand-side flexibility can play a big role in the current and future electricity grid, as customers, demand aggregators and grid operators can benefit from these actions. From an operational point of view, the tests in the laboratory showed that the HVAC and the battery were able to follow the activations received, as long as the commands were properly calculated by the aggregator. For the Scenario 1, the aggregator modified the temperature setpoint of the HVAC, causing a shift of the consumption to different time periods. In the Scenario 2, the battery charge/discharge power setpoint was modified by the aggregator in order to reduce the electricity consumption from the grid or inject power into it when necessary. From the customer’s perspective, we saw that the DR actions can increase the energy cost in some cases, highlighting the importance of economic incentives to attract customer engagement. In addition, in the Scenario 1, involving the HVAC system, the thermal comfort of the users was not affected by the presence of the aggregator, as the indoor temperatures were maintained in an adequate range. Finally, allowing the aggregator to control the battery in Scenario 2 did not have any effect on the self consumption factor of the user. Regarding OpenADR, a test was developed first virtually and then between the laboratory and the aggregator in Scenario 3. OpenADR proved to be a reliable and useful protocol that has the potential to be used in DR applications due to the different use cases it can cover
