Comparison of smart control strategies for heat pumps

Abstract

As a side effect of the energy transition, the Netherlands experiences severe grid congestion. This can be mitigated by distributing the load on the grid more evenly over time. Heat pumps are a major contributor to the grid load. Different smart control strategies have been developed for load shifting of heat pumps. The aim of this projectwas to quantify the grid congestion mitigation potential of heat pumps in theNetherlands for different smart control strategies, and to identify the barriers to the implementation of each smart control strategy. This was achieved by comparing a set of promising smart control strategies in a simulation of a typical Dutch neighborhood. Different scenarios were used to determine the effectiveness of each strategy in situations with more or less heat pumps, varying insulation levels for the houses, and a range of smart control adoption rates. Seven control strategies were compared, with varying complexity. The results of the simulations show that the constant heating strategy and model predictive strategy with day-ahead pricing have the best grid congestion mitigation potential in scenarios with a high heat pump adoption rate. The constant heating strategy however results in an increase in electricity usage and costs for the heat pump of up to 13%. The model predictive strategy with day-ahead pricing resulted in a decrease instead for the electricity and costs of 15-20%, but is much more complex to implement in practice. In the scenarios with lower heat pump adoption rates the model predictive strategy with "optimal" pricing performed the best, with a reduction in peak loads and costs of up to 30%.