Continually increasing water demand (due to population growth) and fuel costs threaten the reliability of water and energy systems and also increase operational costs. In addition, climatic variability and long-term change increase the vulnerability of these two systems. For instance, reservoir systems primarily depend on monthly to seasonal precipitation; whereas power systems demand depend on variations in diurnal temperature over the season. Currently, both systems consider climatological averages for their short-term (0-3 months) management, which ignores uncertainty in the climate resulting in reduced hydropower (i.e., increased spill) from reservoirs and increased operational costs for power systems from excessive fuel stockpiling. While seasonal climate forecasts contain appreciable levels of skill over parts of the US in both winter and summer, the uptake of these forecasts for co-optimization of water and power systems has been limited due to lack of a framework to assimilate, visualize and communicate probabilistic forecasts into management models. The project will develop a prototype visual analytic simulation-optimization framework for better communication and visualization of probabilistic information on the decision space for improving water and power systems sustainability utilizing monthly to seasonal multimodel climate forecasts.
The primary goal of this poject is to develop an integrated cyber-enabled approach for improved water and energy sustainability utilizing the monthly to seasonal climate forecasts by: A. Developing a cyberinfrastructure framework using Optimus-PRIME that co-optimizes water and power system allocations by incorporating precipitation, power demand and wind power ensembles. B. Developing a visual analytic framework for interactive exploration of multi-objective decision space and interaction with the optimization engine by leveraging recent developments in visual analytics. C. Developing fine-grained and coarse-grained resource utilization strategies for targeting different parts of the computation on heterogeneous many-core/accelerator based architectures. D. Analyzing risk management strategies that include improved fuel stockpiling, scheduled plant maintenance and reservoir operational schedules to minimize operational costs utilizing the multimodel electricity demand, wind power, and streamflow forecasts available for the pilot basin. F. Performing scenario analyses that consider increased renewable energy availability -- hydropower and wind -- in the power generation mix, reduced CO2 emission scenarios under current and increased water demand potentials contingent on multimodel climate forecasts. F. Synthesizing the findings from objectives (A-F) by considering various virtual water and power system configurations that are typical across the country for generalization and broader application. The fundamental contribution of the proposal lies in developing a prototype cyberinfrastructure for improving water and power systems management utilizing climate forecasts. Using the framework, the study proposes to minimize the operational costs of these two interdependent systems by considering various scenarios for maximizing the renewable energy potential utilizing multimodel climate (precipitation, temperature and wind) forecasts. By utilizing the streamflow and power demand forecasts, a paradigm shift in water and power systems management is targeted that promotes various proactive strategies such as forward purchasing of fuels, reducing emissions and meeting target reservoir storage to ensure both systems reliability. To overcome the computational challenges arising from probabilistic forecasts, an HPC-enabled cyberinfrastructure will parallelize the computations across ensembles and provide a seamless interaction between water and power stochastic optimization models. For interactive exploration of multi-objective decision spaces in the water and power sectors, new developments in visual analytics will be employed that can lead to improved stakeholder facilitated solutions for the pilot basin and promote learning and understanding through virtual systems.
Developed research modules and findings will be incorporated into various advanced graduate courses at NCSU in the water resources and environmental engineering, computer-aided engineering and power system engineering curricula. The developed climate information based risk-management tools will also be used in the NCSU's Climate Change and Society Professional Science Master's program, which exclusively draws professionals with interdisciplinary background. The investigators will also work with the State Climate Office of NC and federal agencies, PNNL and ORNL, to implement the algorithms developed in the project for broader applications. The investigators will also develop customized podcasts and modules on climate-water-energy nexus and their significance to sustainability for high school students by collaborating with the engineering place at NCSU.
