Energy Management Strategy of Large-scale Hybrid Energy Storage System Based on Layered Optimization
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Energy Management Strategy of Large-scale Hybrid Energy Storage System Based on Layered Optimization
Vol. 44, Issue 4, Pages: 1177-1186(2018)
作者机构:
华北电力大学新能源电力系统国家重点实验室
作者简介:
基金信息:
DOI:
CLC:
Published Online:10 May 2018,
Published:2018
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SU Hao, ZHANG Jiancheng, WANG Ning, et al. Energy Management Strategy of Large-scale Hybrid Energy Storage System Based on Layered Optimization[J]. 2018, 44(4): 1177-1186.
DOI:
SU Hao, ZHANG Jiancheng, WANG Ning, et al. Energy Management Strategy of Large-scale Hybrid Energy Storage System Based on Layered Optimization[J]. 2018, 44(4): 1177-1186.DOI:
Energy Management Strategy of Large-scale Hybrid Energy Storage System Based on Layered Optimization
In accordance with the coordination among different energy storage media and power allocation among parallel-connected energy storage units(ESUs) in the large-scale hybrid energy storage system(HESS)
a double-layer energy management strategy that distributes power step by step with the whole HESS
the medium packs
and the ESUs is proposed.The central distribution layer adopts the improved low-pass filtering algorithm with the state of charge(SOC) of ultracapacitor pack to obtain the power instructions of each pack.By means of state identification and artificial intervention
the algorithm’s disadvantages that easily lead to opposite operation states between medium packs are solved.The introduction to the power limit of battery pack Plimit furthe
r smooths its output.Considering the sustainable scheduling and operation economy of the HESS
the power distribution models of battery units and ultracapacitor units are established
respectively
in the local distribution layer
and the power instructions from the upper layer are further distributed between various ESUs in each pack.Finally the output of an energy storage station at 13:00—13:30 in a day is used as an example to verify the effectiveness of the proposed strategy.The results show that this strategy can reasonably distribute power to every ESU(so that their SOCs remain in 0.4
0
.8)
and save the operating cost of the battery pack about 17.7%.