Battery voltage modeling for portable systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Maximum power transfer tracking for a photovoltaic-supercapacitor energy system
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Hybrid electrical energy storage systems
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
An analytical model for predicting the remaining battery capacity of lithium-ion batteries
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Benefits and limitations of tapping into stored energy for datacenters
Proceedings of the 38th annual international symposium on Computer architecture
DC–DC Converter-Aware Power Management for Low-Power Embedded Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimal control of a grid-connected hybrid electrical energy storage system for homes
Proceedings of the Conference on Design, Automation and Test in Europe
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Photovoltaic (PV) power generation systems are one of the most promising renewable power sources to reduce carbon footprint. Grid-connected PV power systems do not generally have a battery to store the excess charge. However, due to severe imbalance between the peak PV power generation and peak load demand, battery-less Grid-connected PV systems are much less effective for the purpose of power generation and demand mismatch mitigation. Grid-connected PV systems equipped with a battery indeed require elaborate management. This is the first paper that introduces a systematic battery management optimization that accommodates arbitrary electricity billing policies. We formulate an optimization framework to determine the battery charging current from the Grid and PV array taking into account the limited battery capacity, power converter efficiency, battery's internal resistance and rate capacity effect, and maximum power tracking of the PV array. Experimental results show that the proposed algorithm effectively reduces the electricity bill by as much as 28% when compared with previous state-of-the-art battery management policies.