We are on the verge of a global energy system revolution. By signing and ratifying global treaties, the groundwork for this revolution is laid. The objective is to limit global warming to two degrees Celsius above pre-industrial levels and stabilise greenhouse gas concentrations at a level that would prevent dangerous anthropogenic interference with the climate system, before 2050. This requires a carbon-free electricity system, which implicates that existing fossil sources of electricity need to be replaced by renewable sources. Most of these sources are weather-dependent and follow seasonal patterns. This leads to a variable, uncertain, and uncontrollable electricity supply. Energy system integration is posed as a key concept to provide the much-needed flexibility to the electricity grid and has been the subject of extensive research. However, there still is a considerable need for further research in the field of energy system integration. Part of the research gap is validation and substantiation of the proposed energy system integration policies and investment decisions. An indispensable component for filling the research gap is a numerical model of the energy system. In this context, the author of this thesis developed a numerical model of the Dutch high-voltage electricity grid. The model can be used to analyse proposed energy system integration policies, optimise the electricity system investment decisions, and prioritise the bottlenecks in the electricity system. The model is used to analyse the effects of several power and heating sector integration scenarios for 2050. The model is constructed in the pandapower framework. The framework is coded in the Python programming language. The model parameters are based on open data and the model input is derived from national sector outlooks and the Energy Transition Model from Quintel Intelligence. Due to the unavailability of operational data from the reference system, the accuracy of the model is determined by evaluating the underlying assumptions and performing a sensitivity analysis. Once the model is validated, the effects of power and heating sector integration on the Dutch high-voltage electricity grid are analysed and the bottlenecks are identified. The results show a substantial increase in grid loading. The highest grid loading occurs when a large portion of the heating demand is electrified, and a large portion of the electricity supply is generated by variable renewable energy sources. The bottleneck analysis of power and heating sector integration scenarios presents one of the use cases of the created representative model of the Dutch high-voltage electricity grid. As the model is based on open data, it is the intention of the author to make the model publicly available as well. This allows other entities to perform a broad range of analysis on the electricity system.