Now showing items 1-3 of 3

    • Deep reinforcement learning for home energy management system control 

      Lissa, Paulo; Deane, Conor; Schukat, Michael; Seri, Federico; Keane, Marcus; Barrett, Enda (Elsevier, 2021-12-26)
      The use of machine learning techniques has been proven to be a viable solution for smart home energy management. These techniques autonomously control heating and domestic hot water systems, which are the most relevant ...
    • Impact of source variability on flexibility for demand response 

      O'Connell, Sarah; Reynders, Glenn; Keane, Marcus M. (Elsevier, 2021-08-05)
      This paper assesses the quality of the services provided for demand response by analysing the results of experimental work activating flexible sources in buildings, while evaluating the impacts on occupant comfort and ...
    • Transfer learning applied to DRL-Based heat pump control to leverage microgrid energy efficiency 

      Lissa, Paulo; Schukat, Michael; Keane, Marcus M.; Barrett, Enda (Elsevier, 2021-09-11)
      Domestic hot water accounts for approximately 15% of the total residential energy consumption in Europe, and most of this usage happens during specific periods of the day, resulting in undesirable peak loads. The increase ...