發(fā)布時(shí)間：2018-11-06 15:04

【摘要】：為了改善風(fēng)機(jī)出力特性,提出了一種基于超短期風(fēng)電功率預(yù)測的混合儲(chǔ)能控制策略。首先,利用解析模態(tài)分解方法從風(fēng)電信號(hào)中提取低頻信號(hào),采用了一種改進(jìn)布谷鳥方法優(yōu)化支持向量機(jī)的懲罰因子參數(shù)和核函數(shù)參數(shù)進(jìn)行超短期功率預(yù)測;然后,對(duì)低頻預(yù)測信號(hào)建立1 min時(shí)間尺度和30 min時(shí)間尺度的功率波動(dòng)并網(wǎng)指標(biāo),判斷是否觸發(fā)蓄電池動(dòng)作,若動(dòng)作,采用AMD分解自適應(yīng)調(diào)整低頻預(yù)測信號(hào)的截止頻率,直到滿足并網(wǎng)要求,確定蓄電池補(bǔ)償功率指令。最后根據(jù)蓄電池荷電狀態(tài)和補(bǔ)償功率指令自適應(yīng)調(diào)節(jié)原始風(fēng)電信號(hào)截止頻率,高頻信號(hào)通過模糊控制由超級(jí)電容器補(bǔ)償。仿真算例表明,該方法可以有效平滑功率波動(dòng),減少蓄電池的循環(huán)次數(shù),同時(shí)保證了蓄電池儲(chǔ)能的平滑能力,避免過充過放,延長蓄電池的壽命。
[Abstract]:In order to improve the performance of blower, a hybrid energy storage control strategy based on ultra-short term wind power prediction is proposed. Firstly, the low frequency signal is extracted from the wind signal by the analytic mode decomposition method, and an improved Cuckoo method is used to optimize the penalty factor parameter and kernel function parameter of support vector machine for ultra-short term power prediction. Then, the power fluctuation indexes of 1 min time scale and 30 min time scale are established for the low frequency prediction signal to judge whether or not to trigger the battery action. If the operation is done, the cut-off frequency of the low frequency prediction signal is adjusted adaptively by AMD decomposition. Until the grid connection requirements are met, battery compensation power instructions are determined. Finally, the cutoff frequency of the original wind signal is adaptively adjusted according to the charging state of the battery and the compensation power instruction, and the high frequency signal is compensated by the supercapacitor through fuzzy control. The simulation results show that the proposed method can effectively smooth the power fluctuation, reduce the cycle times of the battery, ensure the smooth energy storage ability of the battery, avoid overcharging and overdischarge, and prolong the battery life.
【作者單位】： 華北電力大學(xué)河北省輸變電設(shè)備安全防御重點(diǎn)實(shí)驗(yàn)室;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(51177047)
【分類號(hào)】：TM614

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