Direct drive wave energy converters integrated with a composite energy storage system

2011 ◽  
Author(s):  
Zanxiang Nie ◽  
Xi Xiao ◽  
Hu Yi ◽  
Qing Kang
Keyword(s):  
Energy Storage ◽  
Wave Energy ◽  
Storage System ◽  
Energy Storage System ◽  
Direct Drive ◽  
Wave Energy Converters ◽  
Composite Energy ◽  
Energy Converters

scholarly journals Designing and Testing Composite Energy Storage Systems for Regulating the Outputs of Linear Wave Energy Converters

Energies ◽  
2017 ◽  
Vol 10 (1) ◽  
pp. 114 ◽  
Author(s):  
Zanxiang Nie ◽  
Xi Xiao ◽  
Pritesh Hiralal ◽  
Xuanrui Huang ◽  
Richard McMahon ◽  
...  
Keyword(s):  
Energy Storage ◽  
Wave Energy ◽  
Storage Systems ◽  
Linear Wave ◽  
Energy Storage Systems ◽  
Wave Energy Converters ◽  
Composite Energy ◽  
Energy Converters

Statistical Energy Storage Sizing for Point Absorber Wave Energy Converters (WECs): A Device for Operation off the U.S. East Coast

2018 ◽  
Author(s):  
Xiang Zhou ◽  
Mehdi Jafari ◽  
Ossama Abdelkhalik ◽  
Umesh A. Korde ◽  
Lucia Gauchia
Keyword(s):  
Time Series ◽  
Energy Storage ◽  
Wave Energy ◽  
Power Distribution ◽  
Body Wave ◽  
Storage System ◽  
Ground Truth ◽  
Energy Storage System ◽  
Sensing Applications ◽  
Extracted Power

This paper addresses the sizing problem of an energy storage system (ESS) while considering statistical tolerance for a two-body wave energy converter (WEC), which is designed to support ocean sensing applications with sustained power for long-term functioning. The power is extracted by assuming ideal power take-off (PTO) based upon historical ocean data record (significant wave height and period of wave swell) from Martha’s Vineyard Coastal Observatory. A gamma distribution is applied to generate the extracted power distribution of each sample in the time-series using Bayesian methodology. The means and standard deviation of the extracted power distributions compose the statistical annual power time-series. Finally, the required capacities for the ESS sizing are estimated and discussed while considering both ground truth values and statistical values.

scholarly journals State of Charge Estimation of Composite Energy Storage Systems with Supercapacitors and Lithium Batteries

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Wang ◽  
Chunli Liu ◽  
Jianrui Sun ◽  
Kun Zhao ◽  
Licheng Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Kalman Filtering ◽  
Lithium Batteries ◽  
Estimation Error ◽  
Storage System ◽  
Energy Storage System ◽  
Least Square ◽  
Recursive Least Square ◽  
Soc Estimation ◽  
Composite Energy

This paper studies the state of charge (SOC) estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square (RLS) method and Kalman filtering (KF) algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability.

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