All over Europe, the expansion of renewable energy sources is quickly proceeding, fueled by environmental and political motives. The power generated by renewables is heavily subject to the intermittency of the source, e.g. the availability of wind or solar irradiance. Consequently, electrical grids that rely on renewable sources alternate between periods of excess power availability and periods with lack of power production. Excess power is often curtailed or exported, whereas the shortage of power production must be imported or produced through the deployment of more expensive production units. Power-to-X strategies aim to utilise the excess power from renewables more effectively, by converting power to another energy carrier within the grid, e.g. heat or hydrogen. By allowing the transition of power to another energy carrier, the system is transformed into a so-called multi-energy system. Therefore, the system takes into account the multiple energy carrier's system characteristics and loads in an integrated way. This formulation allows for optimal scheduling of energy flows in the system while taking into account characteristics of each energy carrier, e.g., storage characteristics, time-varying costs or production emissions. The main focus of this thesis to deal with the tasks of an energy management system for the aforementioned system using Model Predictive Control. The Model Predictive Control framework allows real-time optimal scheduling while incorporating data-driven forecasts of future loads and generation in the grid. Due to the stochastic nature of these forecasts, this thesis also looks into extensions of Model Predictive Control that can cope with uncertainties. Furthermore, to handle the different timescales of the grid dynamics, Model Predictive Control for multi-timescale systems is investigated. In particular, the performance of a Heuristic Model Predictive Control scheme and a Hierarchical Model Predictive Control scheme on the control of a simulated Power-to-X based energy system are compared. The simulation is based on a conceptual Power-to-X system based on historical data of the Dutch energy sector. Based on this case study, a statement is made about the suitability of the Power-to-X principles to future Dutch sustainable neighbourhoods. Moreover, a statement regarding the economic viability of the presented concept is made based on the simulations.

The pressure on water and energy resources, along with the transition towards new infrastructure, requires an integrated approach to achieve future-proof concepts. A nexus approach can contribute to this by including the interaction between water and energy. This is also known as a water-energy nexus (WEN). Furthermore, when considering decentralization as an ‘infrastructure pathway’, new solutions can be considered where more resources are locally used. Therefore, the circular economy principle was used as a baseline for this research, as it becomes possible to include both water and energy as important resources. There are currently various assessment frameworks that facilitate the decision-making process for different infrastructure pathways. However, it was found that these frameworks do generally not evaluation indicator that go in line with a circular economy approach. This research presents a six-step generic assessment framework that can be used to evaluate different decentralized WEN systems. The first step was formed to give the opportunity in setting up the research scope. It has the possibility to either select one neighborhood as a study case of multiple depending on the research objectives. After that comes a modular step where it is possible to include different innovative technologies that are relevant for a more decentralized WEN system. The water- and energy balance can be modeled in the third step, providing insight into the (re)use of water- and energy sources on different temporal scales. Subsequently, the generic assessment framework contains 13 evaluation indicators that are divided into four themes: (1) water system, (2) value for people, (3) energy system, and (4) general characteristics. The last step includes stakeholder perspectives to prioritize and weigh the indicators. A modern Dutch neighborhood with a high building density (City Nieuwegein) was used as a case study to demonstrate the generic assessment framework. Four scenarios were designed (reference, improved centralized, hybrid, and almost decentralized) to assess the impact of a neighborhood with more decentralized WEN systems. The case study results showed that more decentralization strategies improved most indicator scores. Using different decentralized WEN systems increases the collection and storage of local water- and energy resources. It was found that neighborhoods with more decentralization strategies have a higher complexity (e.g., monitoring and spatial limitations) in implementation. Moreover, the investment- and maintenance costs can be up to 51% higher compared to a neighborhood with minimal decentralized WEN systems. However, the outcomes of the six stakeholder perspectives, showed that the scenario with the highest level of decentralization was, in all cases, preferred. The results of the case study showed that the generic assessment framework can be used to evaluate different decentralized WEN systems. The 13 evaluation indicators followed the circular economy principle as this favors future-proof concepts. Besides, the generic assessment framework included stakeholder perspectives so that it can facilitate the decision-making process of stakeholders. This framework can be further improved by including multi-objective optimization resulting in more scenarios that can be simulated. At last, more research is required for qualitative indicators that improves evaluating the different scenarios.