## 5 Conclusions and Recommendations for Further Research
### Recommendations for Further Research  
In order to obtain more accurate results, a dataset of higher quality is required. With such a dataset, the effect of heat pump power consumption on room temperature can be estimated. With this effect known, households and their temperature behavior could be simulated, mimicking a real-life situation with high accuracy. In so doing, the maximum switch time, non-activity time and compensation algorithm would not be needed. An alternative solution to this approach would be to create a thermodynamic model that simulates household behavior based on insulation values and outside temperature. A sensitivity analysis could investigate the effects of the maximum switching time, non-availability factor and several FCR product specifications on the potential for FCR. The product specifications could be included in the sensitivity analysis to investigate the effect of TSO-regulation on the bidding strategies of aggregator parties. This would require cooperation between the TSO and the aggregator to clearly design the detailed regulations.  
Results show that NA-fines comprise of a stronger limiting factor to the bid size and revenue compared to IR-fines. In practice, this means that the aggregator receives high fines for inability to deliver 100% flexibility, while this situation seldom occurs. Further research should aim to investigate the quality and potential of FCR by DR with a different regulation structure.  
The scope of this study lies in the potential for residential heat pumps to offer flexibility on the FCR market. Further research could be performed by extending the model to operate on other markets or other technologies as well. In the Netherlands, the model could be extended to secondary or tertiary reserves, other technologies and the effect of combining different technologies on other markets. Eventually, comparisons could be made between countries and their regulations to determine how the balancing system can be optimized at the European level. The model can be used in a predictive manner, with a given portfolio, to predict in which markets the most profits can be achieved.  
In this study, a portfolio is used consisting solely of residential heat pumps. In practice, given the high seasonal dependency and the fact that combining heat pumps with other DR-assets will increase the potential for FCR, it is unlikely that an aggregator will bid on the FCR market with a portfolio consisting solely of heat pumps. Future research may focus on combining the heat pumps in an integrated DR portfolio, thereby increasing the overall potential.  
[PERSON] developed the model and performed the experiments. [PERSON], [PERSON], [PERSON] and [PERSON] together defined the problem, formulated the research goal, revised the model, analyzed the results and wrote the paper.  
This project is part of the PVProsumers4 Grid Project, which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 764786. Furthermore, this work has received funding in the framework of the joint programming initiative ERA-Net Smart Grids Plus as part of the CESEPS project.  
The authors declare no conflict of interest.