Uncertainty-aware simulation-optimization framework for water-energy systems

The water-energy nexus plays a crucial role in fostering sustainable growth, since it is the cornerstone for the interconnected and intertwined systems of water and energy supply, consumption, and management. This interrelation is the paramount for achieving sustainable development goals, as both water and energy resources are essential for economic growth, social prosperity, and environmental stewardship. In this respect, this Ph.D. thesis explores, describes and quantifies the complex interdependencies within the water-energy nexus, focusing on the incorporation and management of uncertainty arising from both aleatory and epistemic sources. The research investigates the impacts of climatic variability, social dynamics, and energy market fluctuations on water-energy systems, with a particular emphasis on optimizing system performance under uncertain conditions. Since, the water-energy nexus is driven by inherently uncertain hydroclimatic processes and multiple human-induced procedures (e.g., legal regulations, strategic management policies, real-time controls, market rules), it is globally recognized that their operation is highly exposed to emerging climatic, anthropogenic, and energy-market pressures and fluctuations. In this respect and to move forward fragmented approaches, we aim at establishing an uncertainty-aware simulation-optimization framework that support systems for water planning and management, under the holistic prism of water-energy-society nexus. This shift will require an effective and efficient integration of different theories , i.e., the triptych of statistics, stochastics and copulas and tools, i.e., simulation, optimization and agent-based models into a unified methodological framework. In particular, this framework seeks for the combined effects of the climatic, social and energy market uncertainties within the water-energy nexus, as well as the interplay of their cascades and dependencies that have received considerably less attention to date. For the description of climatic and energy market uncertainty, we are taking advantage of stochastic models, while for the representation of the social dynamics within the technical systems we employ statistical analyses and agent-based models. Through a combination of advanced simulation techniques and optimization procedures, this research identifies uncertainty-aware strategies for adaptive management and decision-making, that affect the system’s performance, as quantified in terms of economy, reliability and resilience. The uncertainty-aware simulation-optimization framework for water-energy systems is stress-tested at three scales of interest: (a) the design scale, aiming at the optimal sizing and mixing of small hydropower plants; (b) the long-term management scale, aiming at assessing the policies of water utilities, under changing hydroclimatic and socioeconomic conditions; and (c) the combination of short, mid and long-term scale, aiming at defining their optimal operation policy under changing hydroclimatic and socioeconomic conditions, also dominated by issues of scheduling of energy production under uncertain energy market fluctuations. For the validation of the concepts, methodologies and tools a series of hypothetical and rea l- world cases are examined covering a wide range of spatial and temporal scales. Overall, this research contributes to the emerging field of water-energy nexus by addressing the challenges posed by uncertainty and variability across multiple domains. Eventually, the findings offer valuable insights and toolboxes for policymakers, planners, and stakeholders involved in managing and optimizing water and energy resources in a changing and uncertain environment.