Optimalisatie van Residentiële PV-Batterijsystemen: Van Verliesmodellen tot Investeringsbeslissingen

Renewable energy generation is key in mitigating climate change, by reducing the greenhouse gas emissions of the present and future electricity consumption, due to the electrification of heating and transportation. On the residential level, this has led to the adoption of PV systems. PV-battery systems offer one way of enabling additional distributed generation, as these allow to store excess PV generation, reducing the stress on the grid. In the past, the adoption of PV systems was characterized by boom-and-bust cycles due to changing policies. This highlights the importance of understanding the impact of a certain context on a household's investment decision. By determining a household's optimal cost-efficient PV-battery system, and by delivering insights to policymakers on how these systems contribute to their objectives, and to distribution system operators on how these systems impact the stress on the grid, a smooth adoption of PV-battery systems can be ensured. To maximize the potential of PV-battery systems, this thesis aims to determine the optimal sizing and operation of a residential PV-battery system. First, the accuracy of the existing efficiency guidelines for PV-battery systems is evaluated. These are found to be insufficient for DC-coupled systems, as only singular power flows are measured. Therefore, a new measurement procedure was proposed, which measures the complete operating range of the converter, including the combined power flows. These measurements allowed to fit a high-fidelity quadratic power-dependent loss model. The higher the prevalence of combined power flows during operation, the greater the need for these high-fidelity loss models. Then, the need for more accurate loss models in PV-battery system optimization is assessed by comparing the optimization results of optimization models which implement linear loss models, as generally found in the literature, and the developed optimization model, which integrates a more accurate converter and battery loss model using convex relaxations. This model simultaneously optimizes the sizing and operating of a PV-battery system. When comparing the linear and the convex optimization model, there is a trade-off between model accuracy and computational tractability. The results of the convex optimization offer the same accuracy as the non-linear implementation, for a runtime of a factor six lower. The linear optimization further decreases this runtime, but the cost objective is underestimated by 17%. By applying the convex optimization model to study the investment decisions of 200 households when the network tariff changes from volumetric to capacitybased, and electricity prices increase, insights can be derived for households, distribution system operators and policymakers. In scenarios with high feed-in remuneration, especially when the remuneration was higher than the levelized cost of electricity, households could achieve a net benefit and would be best to maximize their installed PV capacity. The main investment drivers for households were the reduction of grid withdrawal and feed-in remuneration. The objective of the distribution system operation, to reduce the burden shifting from prosumers to consumers, was achieved as prosumers contributed more under the capacity-based tariff compared to the volumetric tariff. Households that become prosumers contribute to the targets set by policymakers to reduce carbon emissions and increase renewable energy capacity. Although a capacitybased network tariff leads to lower emission reductions by prosumers compared to volumetric network tariffs, it increases fairness and cost-reflectivity for both prosumers and consumers. Finally, the impact of future trends on the adoption of PV-battery systems is studied. In the future, household electrification will result in a larger battery size and the investment driver related to the reduction of grid withdrawal will gain importance. As the battery price decreases past a certain tipping point, DC-coupled PV-battery systems are preferred to AC-coupled battery systems, as these are more cost-efficient and enable a larger installed PV capacity for the same inverter size. To conclude, the measurement procedure presented in this thesis demonstrated the importance of measuring combined power flows when determining the efficiency of DC-coupled PV-battery systems. The procedure could serve as an addition to future efficiency standards. The convex optimization then demonstrated that integrating more accurate loss models into PV-battery system optimization models is computationally tractable and has a tangible impact on the objective. This optimization model could serve as a valuable tool for households, distribution system operators and policymakers. By applying this tool, households can install the most cost-efficient PV-battery system for their homes, distribution system operators can gain insights into how a household's investment decision impacts the recovery of the grid costs as well as the grid stability, and policymakers can better understand how prosumers contribute to their policy objectives.