Flexibility deployment of a heating system with heat pump in residential towers
Keywords:Energy flexibility, heat pump operation, thermal mass, thermostat setpoints, electricity price scenarios
The transition from fossil fuel energy sources to renewable energy sources requires flexible use of our energy consumption to prevent congestion in the electricity grid. The heating systems of buildings are large energy consumers and can play an important role in matching electricity generation and demand. This research evaluates the amount and value of the potentially available flexibility from the heat pump in a case study on the heating system of two residential towers in The Netherlands, named Stoker & Brander. The thermal mass of the buildings is used to store energy to prevent heating during moments when grid congestion is likely to occur or when renewable energy production is low while maintaining comfortable indoor temperatures. To assess the potential energy flexibility, a building performance model and a financial model are developed to compare the influence on the energy flexibility when using different thermostat setpoint schedules. The total heat demand, the shifted load, the comfort, and the saved costs when deploying flexibility are selected as key performance indicators. With the model, 9 different thermostat setpoint schedules are tested with varying preheating duration and with varying timing before peak hours. In general, the schedules with a 2-hour preheating duration show the best results in terms of comfort and potential saved costs, while the timing before the peak hours has less effect on the results. The analysis on the saved costs is done with electricity prices of 2019, representing the current market, and with 4 price scenarios for 2030, representing the future market. The savings significantly increase for 2030, showing a large future potential for flexible deployment. However, it remains difficult to make a correct estimation of the predicted future savings as the scenarios show large differences between each other due to large uncertainty about the future prices. Nevertheless, for all scenarios at least 20% of the electricity purchase costs can be saved in 2030.
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