Solar Power Smoothing in a Nanogrid Testbed
Hossein Panamtash, Rubin York, Paul Brooker, Justin Kramer, Qun Zhou, Sun

TL;DR
This paper explores methods to smooth solar power output in a nanogrid using battery storage and EV charging control, improving grid stability amid high solar penetration.
Contribution
It introduces new control algorithms for solar smoothing utilizing batteries and EVs, tested in a real nanogrid environment with real and forecast data.
Findings
Effective solar smoothing achieved with proposed control methods.
Comparison of real-time and predictive control models.
Validation of models on actual nanogrid data.
Abstract
High penetration of solar power introduces new challenges in the operation of distribution systems. Considering the highly volatile nature of solar power output due to changes in cloud coverage, maintaining the power balance and operating within ramp rate limits can be an issue. Great benefits can be brought to the grid by smoothing solar power output at individual sites equipped with flexible resources such as electrical vehicles and battery storage systems. This paper proposes several approaches to a solar smoothing application by utilizing battery storage and EV charging control in a "Nanogrid" testbed located at a utility in Florida. The control algorithms focus on both real-time application and predictive control depending on forecasts. The solar smoothing models are then compared using real data from the Nanogrid site to present the effectiveness of the proposed models and compare…
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Taxonomy
TopicsSmart Grid Energy Management · Optimal Power Flow Distribution · Microgrid Control and Optimization
