Dispatch Planning of a Wide-Area Wind Power-Energy Storage Scheme Based on Ensemble Empirical Mode Decomposition Technique

Li, Mengting; Li, Yang; Choi, S.S.

doi:10.1109/tste.2020.3042385

Cited by 29 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Liu et al [27] proposed a capacity configuration method considering the lifetime of Liion batteries and determined the optimal capacity of the energy storage system by a multi-objective dynamic planning algorithm. Gao et al [28] and Li et al [29] used an improved complete ensemble empirical modal decomposition with adaptive noise for time-frequency analysis of power fluctuation to determine the optimal cut-off frequency and the corresponding energy storage configuration scheme. Mohseni et al [30] used FCs and SCs to construct HESS in Feilding, New Zealand.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system based on APA‐MOHHO

Lu,

Du,

Zhu

et al. 2024

IET Renewable Power Gen

View full text Add to dashboard Cite

A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system (H‐S HESS) has been proposed in this study for wind power fluctuation suppression. The proposed system consists of a supercapacitor array and a hydrogen energy storage unit, and the bi‐level planning strategy consists of an Energy Management Level and a Capacity Configuration Level. In the upper level, with Hilbert–Huang transform frequency analysis, a novel energy management strategy based on adaptive power allocation (APA) is designed. The lower level applies multi‐objective Harris hawks optimizer to solve the optimal parameters of each device in the system. Based on the data measured from a 2‐MW wind system in a hydrogen‐electric coupled DC microgrid demonstration project, the optimal system capacity configuration scheme is obtained. The annualized cost of the system is $150,212, which is 41.1% lower than the scheme without optimization. The fluctuation unsuppressed rate of H‐S HESS is 0.64% under the APA strategy, which is only 0.14% higher than the conventional HESS (supercapacitor + lithium‐ion batteries) with the same annualized cost of system. The proposed strategy reduces the frequency of HESS operational power fluctuations, improves capacity configuration accuracy, and significantly decreases the cost gap between the proposed H‐S HESS and conventional structures.

show abstract

Section: Introductionmentioning

confidence: 99%

“…[28] and Li et al. [29] used an improved complete ensemble empirical modal decomposition with adaptive noise for time‐frequency analysis of power fluctuation to determine the optimal cut‐off frequency and the corresponding energy storage configuration scheme. Mohseni et al.…”

Section: Introductionmentioning

confidence: 99%

A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system based on APA‐MOHHO

Lu,

Du,

Zhu

et al. 2024

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…The DFT assumes smooth datasets, facing challenges with the non-stationary nature of renewable energy sources. Selecting the appropriate mother wavelet is also a challenge when using the DWT [21]. Although the EMD is a better choice, it comes with mode mixing and disparate amplitude issues in the intrinsic mode functions (IMFs) [19,20].…”

Section: Introductionmentioning

confidence: 99%

“…Although the EMD is a better choice, it comes with mode mixing and disparate amplitude issues in the intrinsic mode functions (IMFs) [19,20]. To tackle such issues, the complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed in [21,22], providing a resolution to the challenges encountered in EMD. Although this method enhances the classification of IMFs using an improved empirical approach, there is room for further improve.…”

Section: Introductionmentioning

confidence: 99%

An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Ye,

Sun,

Song

2024

Energies

View full text Add to dashboard Cite

The integration of a renewable energy and hybrid energy storage system (HESS) into electrified railways to build an electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the effectiveness of the energy management for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow in the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

show abstract

“…Although the EMD is a better choice, it comes with mode mixing and disparate amplitudes issues in the intrinsic mode functions (IMFs) [24,25]. To tackle such issues, the complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed in [26], providing a resolution to the challenges encountered in EMD. Nevertheless, this method enhances the classification of IMFs using an improved empirical approach, there is room for further improve.…”

Section: Introductionmentioning

confidence: 99%

An Energy Management Strategy for Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Ye,

Sun,

Song

2023

Preprint

View full text Add to dashboard Cite

The integration of renewable energy and hybrid energy storage system (HESS) into electrified railways to build electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the energy management effectiveness for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow among the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

show abstract

Dispatch Planning of a Wide-Area Wind Power-Energy Storage Scheme Based on Ensemble Empirical Mode Decomposition Technique

Cited by 29 publications

References 38 publications

A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system based on APA‐MOHHO

A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system based on APA‐MOHHO

An Energy Management Strategy for an Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

An Energy Management Strategy for Electrified Railway Smart Microgrid System Based on Integrated Empirical Mode Decomposition

Contact Info

Product

Resources

About