Fluctuation feature extraction of wind power

Miao, Fufeng; Tang, Xisheng; Qi, Zhen

doi:10.1109/isgt-asia.2012.6303279

Cited by 8 publications

(5 citation statements)

References 15 publications

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Section: Analysis Of Suppression Effect Of Wind Power Fluctuationmentioning

confidence: 99%

“…As seen from Figure 9, after WPD, the maximum power fluctuation at a 1 min time scale is reduced from 12.04 MW to 4.83 MW, so the grid-connected power meets the standard in Table 1. With the calculation method in [20], it can be obtained that the HESS suppresses 67.8% of the wind power fluctuation, so the grid-connected power has an obvious smoothing effect. In order to demonstrate the general applicability of adaptive WPD in different wind power application scenarios, the typical daily output data of 25 MW, 60 MW and 100 MW wind farms are selected for analysis.…”

Section: Analysis Of Suppression Effect Of Wind Power Fluctuationmentioning

confidence: 99%

“…An evaluation index based on intermittent power supply fluctuation and micro-grid supply and demand balance was established, and a HESS charge-discharge method on the basis of WPD and fuzzy control were presented in [18], which can improve the fluctuation of intermittent power supply in micro-grid and reduce unbalanced power. Fuzzy logic control was used to control the energy management system with HESS priority order in [19,20], which can control SOC at a normal level.…”

Section: Introductionmentioning

confidence: 99%

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Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

et al. 2023

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A hybrid energy storage system (HESS) can effectively suppress the high and low-frequency power fluctuations generated by wind farms under the intermittency and randomness of wind. However, for the existing power distribution strategies of HESS, power-type and energy-type energy storage have the problem of inconsistent charge–discharge states in the same time sequence, which makes it difficult to achieve optimal operation in terms of charge–discharge coordination and energy flow. To solve this problem, this study firstly adopts adaptive wavelet packet decomposition (WPD) to decompose the original wind power to acquire grid-connected power and HESS initial distribution power, to ensure that the supercapacitor and battery undertake the corresponding high and low-frequency power fluctuations, respectively; Then, for the inconsistent charge–discharge states, a charge–discharge time sequence optimization strategy based on the consistency index is proposed to correct the initial power distribution of HESS for the first time; Finally, aiming at the stage of charge (SOC) over-limit problem, the fuzzy optimization method is adopted to correct the HESS output power for the second time, which can reduce the unnecessary charge–discharge energy effectively. With typical daily output data of a 100 MW wind farm, the proposed control strategy is verified. The results show that it can make different energy storage technologies synchronously suppress wind power fluctuation in the same time sequence; compared with not considering charge–discharge time sequence optimization, the charge–discharge conversion times of the battery obtained by the proposed method are reduced from 71 to 14 times, and the charge–discharge conversion times of supercapacitor are reduced from 390 to 61 times; The cumulative reduction of unnecessary charge–discharge energy by HESS is 12.12 MWh. Besides, the SOC curves of HESS are controlled at a normal level, thus improving the economy and service life of HESS.

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Section: Analysis Of Suppression Effect Of Wind Power Fluctuationmentioning

confidence: 99%

Section: Analysis Of Suppression Effect Of Wind Power Fluctuationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

et al. 2023

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“…To reflect the fluctuation of wind power accurately, a stability index is defined [22], which reveals the stability of the output power change in the given time window. The specific definition is shown as follows [25]:…”

Section: Effects Of Three Energy Storage Technologies On Suppressing ...mentioning

confidence: 99%

Comparison of Dynamic Response Characteristics of Typical Energy Storage Technologies for Suppressing Wind Power Fluctuation

hong

2023

Sustainability

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The intermittence and randomness of wind speed leads to the fluctuation of wind turbine output power. In order to study the applicability of battery, super capacitor and flywheel energy storage technology in suppressing wind power fluctuation, this paper takes a 3 MW direct drive wind turbine as an example, and, through the establishment of a wind storage system model, the dynamic response characteristics and application effects of the three typical energy storage technologies to suppress the power fluctuation of the wind turbine under two wind speed fluctuation scenarios are simulated and studied, and the stability of output power is quantitatively analyzed. Results show that all the three energy storage systems respond well to power command curves, but when the wind power fluctuation is large, the flywheel energy storage has a better effect on suppressing the wind power fluctuation, which can suppress about 70% of the power fluctuation.

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“…Compared to the other traditional analysis methods in time and frequency domain, the HHT method is adaptive, and it can reflect the partial feature of the signals, which make it more suitable for the wind power fluctuation feature extraction [4]. Therefore, this study will use the HHT method to extract wind power fluctuation feature.…”

Section: Introductionmentioning

confidence: 99%

Research on Wind Power Fluctuation and its Impacts on Power System Frequency

Guo

Miao

Tang

et al. 2013

AMM

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The output power of wind farms has significant randomness and variability, which results in adverse impacts on power system frequency stability. This paper extracts wind power fluctuation feature with the HHT (Hilbert-Huang Transform) method. Firstly, the original wind power data was decomposed into several IMFs (Intrinsic Mode Functions) and a tendency component by using the EMD (Empirical Mode Decomposition) method. Secondly, the instantaneous frequency of each IMF was calculated. On this basis, taking a WSCC 9-bus power system as benchmark, the impact on power system frequency caused by wind power fluctuation was simulated in a real-time simulation platform, and the key component which results in the frequency deviation was found. The simulation results validate the wind power fluctuation impacts on frequency deviation, underlying the following study on power system frequency stability under the situation of large-scale intermittent generation access into the grid.

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Fluctuation feature extraction of wind power

Cited by 8 publications

References 15 publications

Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

Comparison of Dynamic Response Characteristics of Typical Energy Storage Technologies for Suppressing Wind Power Fluctuation

Research on Wind Power Fluctuation and its Impacts on Power System Frequency

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