scholarly journals Power Distribution Strategy Based on Low-Pass Filter Controller with a Variable Time Constant in Hybrid Energy Storage Systems

Author(s):  
Yang Jiao ◽  
Daniel Mansson
2021 ◽  
Vol 12 (4) ◽  
pp. 209
Author(s):  
Hang Li ◽  
Taike Yao ◽  
Xuan Zhang ◽  
Feifei Bu ◽  
Luhui Weng

To solve the problem of severe DC bus voltage fluctuations caused by frequent changes in the distributed electric propulsion aircraft load, and to further optimize the size and life of the hybrid energy storage system (HESS), this paper proposes a method based on three-step power distribution (TSPD). This strategy realizes the reasonable distribution of battery and supercapacitor power by using a low pass filter. Through the introduction of a supercapacitor state-of-charge (SOC) automatic recovery control and maximum power value dynamic limit strategy, the size of the HESS is optimized, and the service life of the energy storage device is extended. Finally, simulation and experiment platform are built to prove the effectiveness of the proposed strategy.


2020 ◽  
Vol 15 (4) ◽  
pp. 496-505 ◽  
Author(s):  
Yu Zhang ◽  
Zhe Yan ◽  
Cui Cui Zhou ◽  
Tie Zhou Wu ◽  
Yue Yang Wang

Abstract The hybrid energy storage system (HESS) is a key component for smoothing fluctuation of power in micro-grids. An appropriate configuration of energy storage capacity for micro-grids can effectively improve the system economy. A new method for HESS capacity allocation in micro-grids based on the artificial bee colony (ABC) algorithm is proposed. The method proposed a power allocation strategy based on low pass filter (LPF) and fuzzy control. The strategy coordinates battery and supercapacitor operation and improves the battery operation environment. The fuzzy control takes the state of charge (SOC) of the battery and supercapacitors as the input and the correction coefficient of the time constant of the LPF filter as the output. The filter time constant of the LPF is timely adjusted, and the SOC of the battery and supercapacitor is stable within the limited range so that the overcharge and over-discharge of the battery can be avoided, and the lifetime of the battery is increased. This method also exploits sub-algorithms for supercapacitors and battery capacity optimization. Besides, the Monte Carlo simulation of the statistic model is implemented to eliminate the influence of uncertain factors such as wind speed, light intensity and temperature. The ABC algorithm is used to optimize the capacity allocation of hybrid energy storage, which avoids the problem of low accuracy and being easy to fall into the local optimal solution of the supercapacitors and battery capacity allocation sub-algorithms, and the optimal allocation of the capacity of the HESS is determined. By using this method, the number of supercapacitors required for the HESS is unchanged, and the number of battery is reduced from 75 to 65, which proves the rationality and economy of the proposed method.


2013 ◽  
Vol 448-453 ◽  
pp. 2799-2806
Author(s):  
Ming Ding ◽  
Jia Xie

The intermittency and volatility of wind power has brought adverse effects on the large-scale wind power integration. The hybrid energy storage system coordinated with wind farms has been set up in order to reduce the volatility of output power of wind farms strongly. The allocation plan between high-frequency and low-frequency wind power can be determined with low-pass filter method in order to determine the restraining target of different energy storage devices. According to the capacity and the state of charge of the batteries and super capacitor, the power reference values can be corrected with fuzzy adaptive control method and exceeded power deviation of the target would be allocated between the two kinds of energy storage devices. The reasonableness of the proposed models is verified by case study results.


Author(s):  
Jianwei Li ◽  
Hongwen He ◽  
Zhongbao Wei ◽  
Xudong Zhang

AbstractThis paper proposes a hierarchical sizing method and a power distribution strategy of a hybrid energy storage system for plug-in hybrid electric vehicles (PHEVs), aiming to reduce both the energy consumption and battery degradation cost. As the optimal size matching is significant to multi-energy systems like PHEV with both battery and supercapacitor (SC), this hybrid system is adopted herein. First, the hierarchical optimization is conducted, when the optimal power of the internal combustion engine is calculated based on dynamic programming, and a wavelet transformer is introduced to distribute the power between the battery and the SC. Then, the fuel economy and battery degradation are evaluated to return feedback value to each sizing point within the hybrid energy storage system sizing space, obtaining the optimal sizes for the battery and the SC by comparing all the values in the whole sizing space. Finally, an all-hardware test platform is established with a fully active power conversion topology, on which the real-time control capability of the wavelet transformer method and the size matching between the battery and the SC are verified in both short and long time spans.


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