Optimal power management with guaranteed minimum energy utilization for solar energy harvesting systems

In this work, we present a formal study on optimizing the energy consumption of energy harvesting embedded systems. To deal with the uncertainty inherent in solar energy harvesting systems, we propose the Stochastic Power Management (SPM) scheme, which builds statistical models of harvested energy based on historical data. The proposed stochastic scheme maximizes the lowest energy consumption across all time intervals while giving strict probabilistic guarantees on not encountering battery depletion. For situations where historical data is not available, we propose the use of (i) a Finite Horizon Control (FHC) scheme and (ii) a non-uniformly scaled energy estimator based on an astronomical model, which is used by FHC. Under certain realistic assumptions, the FHC scheme can provide guarantees on minimum energy usage that can be supported over all times. We further propose and evaluate a piece-wise linear approximation of FHC for efficient implementation in resource-constrained embedded systems. With extensive experimental evaluation for eight publicly available datasets and two datasets collected with our own deployments, we quantitatively establish that the proposed solutions are highly effective at providing a guaranteed minimum service level and significantly outperform existing solutions.