In order to deal with the fluctuation of wind farm output
ensure the stable operation of power system
and take into account the characteristics of various energy storage devices
a stabilization-frequency modulation strategy based on flywheel-electrochemical hybrid energy storage is proposed. Firstly
according to the typical daily wind power data
the fully adaptive noise ensemble empirical mode decomposition is used to decompose it to obtain the direct grid-connected component of wind power and the hybrid energy storage power task. Secondly
considering the multi-type constraints of the energy storage system
taking the maximum annual overall net income of the wind storage system as the objective function
a capacity optimization configuration model of flywheel-electrochemical hybrid energy storage considering wind power stabilization and frequency modulation is established. Finally
the optimal capacity configuration scheme of hybrid energy storage is obtained by iterative solution of adaptive particle swarm optimization algorithm. The results show that compared with the traditional hybrid energy storage system that only stabilizes the fluctuations of wind power
although the investment cost of this hybrid energy storage system has increased
it will also generate higher frequency regulation benefits
which can effectively give full play to the advantages of energy storage stabilization-frequency regulation
and the average annual overall net income of the system is improved
which proves that the strategy proposed in this paper has better economy and feasibility.
CAPACITY OPTIMIZATION CONFIGURATION OF HYBRID ENERGY STORAGE SYSTEM WITH RETIRED POWER BATTERIES IN WIND FARMS
OPTIMAL ALLOCATION OF WIND FARM ENERGY STORAGE CAPACITY BASED ON GROUP CONTROL STRATEGY
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基于AHP-BCO-GRA的多场景风火氢储三层容量优化配置方法
面向资源集群调控的园区共享储能分布鲁棒优化配置方法
Related Author
Li Peiqiang
Li Xiong
Cai Sun
Zhao Wei
Lei Ertao
Shi Linjun
Duanmu Chenrui
Yang Dongmei
Related Institution
College of Electrical and Information Engineering, Hunan University
Electric Power Research Institute of Guangdong Power Grid Co., Ltd.
College of Energy and Electricity, Hohai University
State Key Laboratory of Smart Grid Protection and Control, Nari Group Corporation
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