2 research outputs found
Long-term experimental study of price responsive predictive control in a real occupied single-family house with heat pump
The continuous introduction of renewable electricity and increased
consumption through electrification of the transport and heating sector
challenges grid stability. This study investigates load shifting through demand
side management as a solution. We present a four-month experimental study of a
low-complexity, hierarchical Model Predictive Control approach for demand side
management in a near-zero emission occupied single-family house in Denmark. The
control algorithm uses a price signal, weather forecast, a single-zone building
model, and a non-linear heat pump efficiency model to generate a space-heating
schedule. The weather-compensated, commercial heat pump is made to act smart
grid-ready through outdoor temperature input override to enable heat boosting
and forced stops to accommodate the heating schedule. The cost reduction from
the controller ranged from 2-33% depending on the chosen comfort level. The
experiment demonstrates that load shifting is feasible and cost-effective, even
without energy storage, and that the current price scheme provides an incentive
for Danish end-consumers to shift heating loads. However, issues related to
controlling the heat pump through input-manipulation were identified, and the
authors propose a more promising path forward involving coordination with
manufacturers and regulators to make commercial heat pumps truly smart
grid-ready