SBIR Phase I:Intelligent Monitoring and Control of Revenue-Critical PV Power Plants

Award Information
National Science Foundation
Award Year:
Phase I
Award Id:
Agency Tracking Number:
Solicitation Year:
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Solicitation Number:
Small Business Information
1153 Bordeaux Dr., Ste 199, Sunnyvale, CA, 94089
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Shahar Ben-Menahem
(650) 248-6223
Business Contact:
Shahar Ben-Menahem
(650) 248-6223
Research Institution:
This Small Business Innovation Research Phase I project seeks to develop new methods and algorithms for the analysis and control of degradations in Photovoltaic (PV) systems. There currently exists widespread, and often undetected, underperformance in PV arrays. Although there are numerous site evaluation and analysis tools used in the design phase of solar cell installations, there is currently a lack of on-line monitoring and diagnostic tools to detect and estimate underperformance and associated control algorithms that can improve performance. Underperforming PV cells can result from a host of inter-related abnormalities including shading, dust build up, hot spots and component failures. To improve performance intelligent control can be used to ameliorate power output degradation via actuation at the module- or module-string-level operating points. The purpose of this proposal is to develop, and test in simulation, a hybrid MAP-MPPT estimation and control algorithm, capable of intelligently modulating the operating point to maximize The broader impact/commercial potential of this project include the enhancement of performance of large scale PV arrays and the ability to better estimate the energy payback time for commercial and residential PV systems enabling further deployment of PV worldwide. Leading revenue-critical, PV power plant owner-operators often utilize dedicated operation centers to monitor walls of computer screens, sometimes with alarm mechanisms triggered by inverters. It is often the case that ad-hoc methods are utilized and decisions are based primarily on operator experience and intuition. Although some sites utilize commercial web-based monitoring services, with industrial grade sensors, this process is far from rigorous, and has resulted in only spotty success. Furthermore, the lack of intelligently controlling the operating point has not yet been fully developed. The proposed solution, used in conjunction with the ability to monitor the state of the PV plant, will correct faults via intelligent control methods enabling optimal power production under degradations for large scale PV arrays. Potential customers are revenue critical solar power sites including: Power Purchase Agreement (PPA) contractors, and lease-holder hosts.

* information listed above is at the time of submission.

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