Water, solar and wind are essential for a sustainable transformation of our energy systems. Distributed solar and wind farms proliferate, but energy harvesting from water is trapped in a century-old damming paradigm with high up-front costs and ecological impacts. And yet, as a river runs down to the ocean, there is enormous amount of kinetic energy that could be sustainably harvested, if done without impoundments that break up the run of the river. An environmentally friendly alternative, known as hydrokinetic or run-of-the-river power extraction, harvests a portion of the kinetic energy in the river at relatively small, local scales at multiple places along the river. However, these projects are characterized by uncertainty in generated output and strong weather/climate dependence. They are typically developed in an ad-hoc manner without prior large-scale analysis of determining optimum locations, online analysis of the produced output, or effective decentralized control of distributed hydrokinetic generators. Furthermore, climate change introduces highly variable weather patterns that alternate benign conditions with catastrophic levels of wind, precipitation, temperature extremes, and droughts.
This project investigates climate-aware modeling, analysis, and control for large-scale sustainable energy harvesting in river networks. The project goals are: (i) modeling of time-space varying river network flow conditions and water levels both with and without multiple hydrokinetic generators; (ii) determining optimum locations for hydrokinetic units in a distributed river network based on economic, reliability-driven, and environmental criteria; (iii) evaluating environmental sensor requirements for demand/response or environmental disaster avoidance; (iv) predictive matching of hydrokinetic power generation and time-varying demand in complex river networks with geospatial and temporal dependencies; and (iv) climate-aware planning for distributed hydrokinetic power generation resources and avoiding catastrophic events.
The potential societal impacts of this research include flood disaster avoidance and guidance on small footprint hydropower project development. Given that the estimated hydrokinetic resource potential in the United States is roughly four times the amount of hydroelectricity currently produced each year, small footprint hydroelectric projects could create enough low-carbon energy to power an economy the size of Virginia's while minimizing the impact to the surrounding environment and nearby communities. While the main goal of the research is determining in a climate-dependent manner the production output and identifying any imbalance between production and demand or the control mechanisms to match one by the other, the approach is sufficiently general to be applied to a more diverse body of applications where deterministic small-scale processes need to be upscaled for effective feedback response and control. The educational and mentoring component incorporates multidisciplinary collaboration across electrical, civil and energy/public policy engineering in creating large-scale complex system models that cross traditional boundaries of both academia and industry. Through its educational component the project involves a diverse student body, while expanding the project's outreach beyond the typical undergraduate and graduate demographics to high-school and middle-school student population.
|Effective start/end date
|9/15/13 → 8/31/17
- National Science Foundation: $227,980.00