Energy

This paper presents two wind energy forecast methods for control of an airborne wind energy system (AWE). The primary objective is to maximize the energy production of the AWE system under a spatio-temporally varying environment with uncertainty in the future wind speed. The controller for the AWE system is formulated as a model predictive controller (MPC). We employ data-driven models to generate probabilistic forecasts of the wind using vector auto-regression (VAR) and time-of-day forecasts. Bayesian optimization is employed to find the optimum of an unknown and expensive to evaluate...

Accurate Lithium-ion (Li-ion) battery internal temperature information enables high-fidelity monitoring and safe operation in battery management systems, thus prevents thermal faults that could cause catastrophic failures. This paper proposes an online temperature estimation scheme for cylindrical Li-ion batteries based on a one-dimensional semilinear parabolic partial differential equation (PDE) model subject to in-domain and output uncertainties, using temperature measurements at the battery surface only. The thermal state observer design exploits PDE backstepping method, with a mild...

This paper focuses on the empirical derivation of regret bounds for mobile systems that can optimize their locations in real-time within a spatiotemporally varying renewable energy resource. The case studies in this paper focus specifically on an airborne wind energy system, where the replacement of towers with tethers and a lifting body allows the system to adjust its altitude continuously, with the goal of operating at the altitude that maximizes net power production. While prior publications have proposed control strategies for this problem, often with favorable results based on...

Numerous innovations emerge for decarbonization in energy systems. Practitioners and policymakers look for reliable methodology to evaluate their actual contributions unbiasedly. Usually, such evaluation starts from extracting a collection of profiles, which represents the actual application scenarios and certainly influences the ultimate results. However, such a fundamental task has seemingly long been treated casually. Limited literature on this topic rarely extends their attention beyond clustering methods. In this paper, we present mainly three innovations. First, we make a systematic...