Hydropower Safety and Efficiency Sensor

Hydropower is increasingly being used as a clean, environmentally friendly alternative to fossil fuel-generated energy. To enhance the performance, value, and safety of hydropower, more accurate data with higher resolution and faster access to real-time data over a wider range of hydrological, environmental, and ecological parameters are being sought using hydrology sensors. These sensors are commonly deployed in various municipalities and scenarios to better understand, account for, and predict water conditions that affect the safety, efficiency, and ecology of generating hydropower. An advanced, more versatile, all-in-one sensor system is needed to provide the foundation for hydropower analytics. The proposed sensor system, consisting of a series of intelligent sensors designed to be robust, accurate, and scalable, monitors a wide range of parameters needed to give a complete understanding of the water characteristics for hydropower. Millimeter-wave radar technology will be used to accurately monitor dam reservoir water levels, riverine discharge, and precipitation, while a two-dimensional imaging sonar sensor will monitor large debris buildup at the dam wall for removal. The sensors will seamlessly send data to an internet-of-things communication module with self-sustaining power monitoring and use open-standard internet protocol to exchange data with any software platform for easy data integration. Additional existing sensor technology will be used to monitor the dam inlet for pressure change to detect clogging from debris, and the sensor expansion port of the communication module will be used to monitor soil moisture. The Phase I development will focus on demonstrating the feasibility of the system, including the millimeter-wave radar sensor and the two-dimensional imaging sonar sensor, their self-sustaining power and communications, and the integration with the existing internet-of-things communication systems including firmware and software. Initial sensor performances will be validated and iterated for seamless transition to a Phase II finalized design and prototype ready for development for more sophisticated machine learning data algorithms in follow-on efforts. The combination of intelligent sensors that can monitor dam reservoir levels, riverine discharge, precipitation and soil moisture, and debris blockage and clogging will provide in-situ performance and safety monitoring for not only the hydropower community, but the flood plain community, water monitoring municipalities, and the first responder and emergency management organizations as well. Competitive advantages include ease of installation by making all sensor platforms wireless with self-contained and self-sustaining power harvesting, reduced overall costs with minimal maintenance using proprietary environmental proofing design methods, open data exchange methods using standard internet protocol for ease of data integration, and smart algorithms for situational alerts.