摘 要:海浪的非平穩(wěn)特性會(huì)影響直驅(qū)式波浪發(fā)電系統(tǒng)能量捕獲,為此提出基于脊線檢測(cè)與變分非線性調(diào)頻模式分解的控制方案。采用短時(shí)傅里葉變換方法分析波浪激勵(lì)力,結(jié)合脊線檢測(cè)設(shè)定初始頻率;應(yīng)用變分非線性調(diào)頻模式分解法分離波浪激勵(lì)力,獲得若干模式分量并提取其瞬時(shí)頻率;通過(guò)計(jì)算各模式分量的能量含量確定主導(dǎo)分量,根據(jù)其瞬時(shí)頻率動(dòng)態(tài)調(diào)整動(dòng)力輸出裝置阻尼,搭建直驅(qū)式波浪發(fā)電系統(tǒng)模型。仿真結(jié)果表明,所提方案能量吸收性能好、輸出平均功率高,可有效改善直驅(qū)式波浪發(fā)電裝置性能。
關(guān)鍵詞:波浪發(fā)電系統(tǒng);波能轉(zhuǎn)換;脊線檢測(cè);變分非線性調(diào)頻模式分解;功率優(yōu)化
中圖分類號(hào):TM619" " " " " " " " " " "文獻(xiàn)標(biāo)志碼:A
0 引 言
“雙碳”戰(zhàn)略關(guān)系國(guó)計(jì)民生和社會(huì)發(fā)展,綠色可再生清潔能源任重道遠(yuǎn)。海洋波浪能是未來(lái)能源的重要組成部分,如何提高其轉(zhuǎn)換效率是波浪能開(kāi)發(fā)的關(guān)鍵技術(shù)之一[1-3]。為此國(guó)內(nèi)外學(xué)者開(kāi)發(fā)了鴨式、衰減式及點(diǎn)吸式等類型波浪能轉(zhuǎn)換器(wave energy converter, WEC)。點(diǎn)吸式WEC又稱直驅(qū)式WEC,將永磁同步直線電機(jī)與隨波浪運(yùn)動(dòng)沉浮的浮子相耦合,直接驅(qū)動(dòng)動(dòng)力輸出裝置(power take off, PTO)獲取功率[2]。
目前的波浪發(fā)電站基本都屬于實(shí)驗(yàn)發(fā)電站,日趨成熟的波浪發(fā)電技術(shù)加快了波浪能項(xiàng)目的商業(yè)化進(jìn)程[4]。波浪發(fā)電系統(tǒng)效率取決于波浪能吸收效率,當(dāng)WEC固有頻率等于入射波頻率時(shí),波浪能捕獲效率最高[5]。實(shí)際海浪具有非平穩(wěn)特性,波浪頻率隨時(shí)會(huì)變,基于單一波浪頻率分析的波浪發(fā)電系統(tǒng)相關(guān)技術(shù)并不能投入實(shí)際應(yīng)用,因此一系列基于不規(guī)則波浪的直驅(qū)式WEC研究應(yīng)運(yùn)而生[6-9]。
文獻(xiàn)[10]提出波浪發(fā)電自適應(yīng)滑??刂疲捎脽o(wú)跡卡爾曼濾波預(yù)估波浪激勵(lì)力的主頻率與幅值,自適應(yīng)滑??刂破鲗⒅彬?qū)式WEC協(xié)調(diào)到最大波能捕獲狀態(tài)。文獻(xiàn)[11]提出基于擴(kuò)展卡爾曼濾波的非線性狀態(tài)估值器(E-EKF)預(yù)估波浪激勵(lì)力、浮子垂蕩位移及速度,結(jié)合機(jī)械阻力和摩擦力,建立直驅(qū)式WEC非線性動(dòng)力學(xué)模型,采用有限集模型預(yù)測(cè)控制策略實(shí)現(xiàn)最大能量捕獲。文獻(xiàn)[12]引入快速傅里葉變換(fast Fourier transform, FFT)分析波浪激勵(lì)力頻譜,將自適應(yīng)快速終端滑模變結(jié)構(gòu)控制與卡爾曼濾波法相結(jié)合,最大限度提高直驅(qū)式WEC的輸出功率。由于實(shí)際海浪的不平穩(wěn)特性,F(xiàn)FT分析無(wú)法獲得實(shí)時(shí)變化的瞬時(shí)頻率,為此文獻(xiàn)[13]采用擴(kuò)展卡爾曼濾波(extended Kalman filter,EKF)、自適應(yīng)濾波[14]、希爾伯特黃變換(Hilbert-Huang transform, HHT)[15]方法估計(jì)實(shí)際海浪的瞬時(shí)頻率,對(duì)比其對(duì)WEC性能的影響,實(shí)驗(yàn)結(jié)果表明采用HHT方法的WEC波能轉(zhuǎn)換效率更高。HHT方法是將經(jīng)驗(yàn)?zāi)B(tài)分解與希爾伯特變換相結(jié)合,但前者的模態(tài)混疊現(xiàn)象使得HHT估計(jì)的實(shí)際海浪激勵(lì)力瞬時(shí)頻率存在誤差。Dragomiretskiy等[16]提出變分模態(tài)分解方法,雖可減少分解模態(tài)混疊現(xiàn)象,但無(wú)法獲取信號(hào)時(shí)頻信息(例如瞬時(shí)幅度與瞬時(shí)頻率)。文獻(xiàn)[17]提出變分非線性調(diào)頻模式分解(variational nonlinear chirp mode decomposition, VNCMD)方法,通過(guò)分析原始信號(hào)的時(shí)頻分布,以識(shí)別的時(shí)頻信息作為各模式分量的初始瞬時(shí)頻率、幅值,通過(guò)解調(diào)技術(shù),迭代更新各模式分量的時(shí)頻信息,將多變量非線性調(diào)頻信號(hào)分離為若干窄帶信號(hào)。
本文針對(duì)隨機(jī)海況的非平穩(wěn)特性,提出脊線檢測(cè)與基于變分非線性調(diào)頻模式分解方法的直驅(qū)式波浪發(fā)電系統(tǒng)控制方案。首先,采用VNCMD方法分解隨機(jī)波浪激勵(lì)力,獲得若干模式分量并提取其時(shí)頻信息;然后,通過(guò)分析各模式分量的能量含量確定主導(dǎo)分量;最后,根據(jù)主導(dǎo)分量的瞬時(shí)頻率動(dòng)態(tài)調(diào)整動(dòng)力輸出裝置阻尼,搭建直驅(qū)式波浪發(fā)電系統(tǒng)模型。仿真結(jié)果表明,所提方案可有效改善波浪發(fā)電裝置性能,直驅(qū)式WEC的波能轉(zhuǎn)換效率有所提高。
1 直驅(qū)式波浪發(fā)電系統(tǒng)
1.1 直驅(qū)式波浪發(fā)電系統(tǒng)
浮子隨波浪浮沉振蕩運(yùn)動(dòng)以提取波浪能量[18],直驅(qū)式WEC裝置如圖1所示。
直驅(qū)式波浪發(fā)電系統(tǒng)VNCMD控制策略流程如圖2所示。
3 實(shí)驗(yàn)分析
在Matlab/Simulink平臺(tái)搭建直驅(qū)式WEC系統(tǒng),參數(shù)設(shè)置為:電感0.0082 H,電阻2.48 Ω,極對(duì)數(shù)4,極距0.1 m,永磁體磁鏈0.147 WB。應(yīng)用ANSYS軟件分析浮子,附加質(zhì)量系數(shù)和輻射阻尼系數(shù)分析結(jié)果如圖3所示。
波浪激勵(lì)力由函數(shù)發(fā)生器隨機(jī)生成,時(shí)長(zhǎng)為64 s,采樣間隔0.01 s,如圖4a所示。選用STFT方法分析波浪激勵(lì)力,時(shí)頻分布結(jié)果如圖4b所示。
采用VNCMD方法分解隨機(jī)波浪激勵(lì)力,由于該信號(hào)由密集模式組成,選擇較小的懲罰參數(shù)減輕相鄰模式之間干擾[17]。相關(guān)參數(shù)設(shè)定:最大頻率變化[Δf=1] Hz;采樣頻率[fs=100] Hz;濾波帶寬為[fs/80][23];比例因子[γ=0.5];分解數(shù)[K=2];懲罰因子[α1=e-8]及[α2=e-11];收斂容差為[e-7];方差[σ=0]。
為驗(yàn)證VNCMD控制策略對(duì)直驅(qū)式波浪發(fā)電系統(tǒng)變量的影響,分別采用HHT控制、VNCMD控制與恒阻尼控制方案。實(shí)際海況中的風(fēng)浪可歸類為高斯隨機(jī)過(guò)程,其統(tǒng)計(jì)特性可通過(guò)頻域和概率域進(jìn)行評(píng)估。因此,PTO可調(diào)諧到波譜的指定頻率,或連續(xù)調(diào)諧到時(shí)變頻率。根據(jù)隨機(jī)波浪激勵(lì)力的波譜能量或峰值頻率,恒阻尼控制策略將系統(tǒng)PTO阻尼設(shè)置為恒定值,其參數(shù)可根據(jù)海況變化定時(shí)調(diào)整,而非逐波調(diào)整[15]。系統(tǒng)最佳阻尼與PTO力對(duì)比結(jié)果如圖5、圖6所示。
由圖5、圖6可知,當(dāng)滿足最大功率捕獲條件時(shí),不同控制策略的最佳阻尼變化不同,所提控制策略的PTO力與其他控制方案略有不同。直驅(qū)式波浪發(fā)電系統(tǒng)捕獲的平均功率及吸收能量對(duì)比結(jié)果如圖7、圖8所示。由圖7、圖8可知,采用恒阻尼控制策略與逐波諧調(diào)最佳阻尼控制策略時(shí),后者需估計(jì)隨機(jī)波浪激勵(lì)力的時(shí)變頻率或能量周期,對(duì)直驅(qū)式WEC性能的改善更為顯著,系統(tǒng)能量吸收更大。所提控制策略與HHT控制策略相比,直驅(qū)式WEC系統(tǒng)平均功率捕獲性能改善2%~15%,波浪能吸收能力提高4%~14%。
4 結(jié) 論
本文通過(guò)分析直驅(qū)式WEC系統(tǒng),針對(duì)海浪運(yùn)動(dòng)特性,提出基于脊線檢測(cè)與變分非線性調(diào)頻模式分解的控制方案。采用脊線檢測(cè)與變分非線性調(diào)頻模式分解方法,分解隨機(jī)波浪激勵(lì)力并提取各模式分量的瞬時(shí)頻率,根據(jù)能量含量選擇主導(dǎo)分量,將系統(tǒng)PTO阻尼諧調(diào)到主導(dǎo)分量瞬時(shí)頻率下的最佳阻尼,實(shí)現(xiàn)WEC系統(tǒng)能量吸收最大化。仿真結(jié)果表明,所提方案可有效改善直驅(qū)式波浪發(fā)電裝置性能,提高系統(tǒng)輸出功率。
[參考文獻(xiàn)]
[1] 洪岳, 潘劍飛, 劉云, 等. 直驅(qū)波浪能發(fā)電系統(tǒng)綜述[J]. 中國(guó)電機(jī)工程學(xué)報(bào), 2019, 39(7): 1886-1900.
HONG Y, PAN J F, LIU Y, et al. A review on linear generator" "based" "wave" "energy" "conversion" systems[J]. Proceedings of the CSEE, 2019, 39(7): 1886-1900.
[2] 邱孟, 楊俊華, 林匯金, 等. 先進(jìn)控制技術(shù)在波浪發(fā)電系統(tǒng)中的應(yīng)用[J]. 電機(jī)與控制應(yīng)用, 2021, 48(2): 13-21.
QIU M, YANG J H, LIN H J, et al. Application of modern control technology in wave energy conversion system[J]. Electric machines amp; control application, 2021, 48(2): 13-21.
[3] 康慶, 肖曦, 聶贊相, 等. 直驅(qū)型海浪發(fā)電系統(tǒng)輸出功率優(yōu)化控制策略[J]. 電力系統(tǒng)自動(dòng)化, 2013, 37(3): 24-29.
KANG Q, XIAO X, NIE Z X, et al. An optimal control strategy for output power of the directly driven wave power generation" "system[J]." "Automation" "of" "electric" "power systems, 2013, 37(3): 24-29.
[4] 肖曦, 擺念宗, 康慶, 等. 波浪發(fā)電系統(tǒng)發(fā)展及直驅(qū)式波浪發(fā)電系統(tǒng)研究綜述[J]. 電工技術(shù)學(xué)報(bào), 2014, 29(3): 1-11.
XIAO X, BAI N Z, KANG Q, et al. A review of the development of wave power system and the research on direct-drive wave power system[J]. Transactions of China Electrotechnical Society, 2014, 29(3): 1-11.
[5] FALNES J, KURNIAWAN A. Ocean waves and oscillating systems:" "linear" "interactions" "including" "wave-energy extraction[M]." "2nd" "edition." "Cambridge:" Cambridge University Press, 2020.
[6] 楊金明, 黃偉. 直驅(qū)式波浪發(fā)電系統(tǒng)的狀態(tài)切換控制方法[J]. 華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版), 2021, 49(2): 1-8.
YANG J M, HUANG W. State switching control method for direct-drive wave power generation system[J]. Journal of South China University of Technology(natural science edition), 2021, 49(2): 1-8.
[7] 盧思靈, 楊俊華, 沈輝, 等. 直驅(qū)式波浪發(fā)電系統(tǒng)的經(jīng)濟(jì)模型預(yù)測(cè)控制[J]. 電測(cè)與儀表, 2021, 58(3): 131-138.
LU S L, YANG J H, SHEN H, et al. Economic model predictive control of direct-drive wave power generation systems[J]. Electrical measurement amp; instrumentation, 2021, 58(3): 131-138.
[8] 吳峰, 王飛, 顧康慧, 等. 基于MEEMD-ARIMA模型的波浪能發(fā)電系統(tǒng)輸出功率預(yù)測(cè)[J]. 電力系統(tǒng)自動(dòng)化, 2021, 45(1): 65-70.
WU F, WANG F, GU K H, et al. Output power prediction of wave energy generation system based on modified ensemble" empirical" mode" decomposition-autoregressive integrated" "moving" "average" "model[J]." Automation" "of electric power system, 2021, 45(1): 65-70.
[9] 黃宣睿, 孫凱, 肖曦. 基于平均功率估算的直驅(qū)海浪發(fā)電最大功率點(diǎn)跟蹤控制方法[J]. 電力系統(tǒng)自動(dòng)化, 2016, 40(14): 51-57.
HUANG X R, SUN K, XIAO X. Maximum power point-tracking" control" method" for" direct-drive" wave" energy generation" " based" " on" " average" "power" "estimation[J]. Automation of electric power systems, 2016, 40(14): 51-57.
[10] 陳海峰, 楊俊華, 沈輝, 等. 基于主頻預(yù)估的波浪發(fā)電系統(tǒng)自適應(yīng)滑模控制[J]. 計(jì)算機(jī)仿真, 2020, 37(3): 94-99.
CHEN H F, YANG J H, SHEN H, et al. Adaptive sliding model control of wave power generation system based on dominant frequency estimation[J]. Computer simulation, 2020, 37(3): 94-99.
[11] JAMA M, MON B F, WAHYUDIE A, et al. Maximum energy capturing approach for heaving wave energy converters using an estimator-based finite control set model predictive" control[J]. IEEE" access," 2021," 9:" 67648-67659.
[12] 黃寶洲, 楊俊華, 沈輝, 等. 基于FFT的直驅(qū)式波浪發(fā)電系統(tǒng)功率優(yōu)化控制[J]. 太陽(yáng)能學(xué)報(bào), 2021, 42(3): 206-213.
HUANG B Z, YANG J H, SHEN H, et al. Power optimization control of drive wave power system based on FFT[J]. Acta energiae solaris sinica, 2021, 42(3): 206-213.
[13] GARCIA-ROSA P B, RINGWOOD J V, FOSSO O B, et al. The impact of time-frequency estimation methods on the performance of wave energy converters under passive and reactive" "control[J]. IEEE" transactions" "on" "sustainable energy, 2019, 10(4): 1784-1792.
[14] CANTARELLAS A M, REMON D, RODRIGUEZ P. Adaptive" vector" control" of" wave" energy" converters[J]. IEEE transactions on industry applications, 2017, 53(3): 2382-2391.
[15] GARCIA-ROSA P B, KULIA G, RINGWOOD J V, et al. Real-time passive control of wave energy converters using the" "hilbert-huang" "transform[J]." "IFAC-papersonline, 2017, 50(1): 14705-14710.
[16] DRAGOMIRETSKIY K, ZOSSO D. Variational mode decomposition[J]." " "IEEE" " "transactions" " "on" " "signal processing, 2014, 62(3): 531-544.
[17] CHEN S Q, DONG X J, PENG Z K, et al. Nonlinear chirp mode decomposition: a variational method[J]. IEEE transactions on signal processing, 2017, 65(22): 6024-6037.
[18] 黃秀秀,楊金明,陳淵睿,等. 基于PCHD模型的振蕩浮子式波浪發(fā)電系統(tǒng)的無(wú)源控制[J]. 電測(cè)與儀表, 2019, 56(7): 107-112.
HUANG X X, YANG J M, CHEN Y R, et al. Passivity based control of oscillating buoy wave power system based on" " PCHD" " model[J]." " Electrical" " measurement" " amp; instrumentation, 2019, 56(7): 107-112.
[19] 劉云鵬, 王江偉, 裴少通, 等. 基于短時(shí)傅里葉變換和稀疏表示的局放識(shí)別分類方法[J]. 電測(cè)與儀表, 2019, 56(23): 31-36.
LIU Y P, WANG J W, PEI S T, et al. Method for identifying and classifying partial discharge based on short time" "Fourier" "transform" "and s" parse" "representation[J]. Electrical measurement amp; instrumentation, 2019, 56(23): 31-36.
[20] 張虹, 徐志豪, 王迎麗, 等. 風(fēng)電場(chǎng)次同步振蕩非線性模態(tài)分解與參數(shù)辨識(shí)[J]. 電網(wǎng)技術(shù), 2022, 46(1): 195-203.
ZHANG H, XU Z H, WANG Y L, et al. Modal identification of subsynchronous oscillation caused by new energy" grid" connection[J]." Power" system" technology, 2022, 46(1): 195-203.
[21] 王麗馨, 蔡國(guó)偉, 楊德友, 等. 基于自適應(yīng)變分模態(tài)分解的電力系統(tǒng)機(jī)電振蕩特征提取[J]. 電網(wǎng)技術(shù), 2019, 43(4): 1387-1395.
WANG L X, CA G W, YANG D Y, et al. Extracting modes from electromechanical oscillation signals for power system based on adaptive variational mode decomposition[J]. Power system technology, 2019, 43(4): 1387-1395.
[22] 趙雅琴, 聶雨亭, 吳龍文, 等. 基于脊路跟蹤的變分非線性調(diào)頻模態(tài)分解方法[J]. 浙江大學(xué)學(xué)報(bào)(工學(xué)版), 2020, 54(10): 1874-1882.
ZHAO Y Q, NIE Y T, WU L W, et al. Multi-component signal separation using variational nonlinear chirp mode decomposition" basednbsp; on" ridge" tracking[J]." Journal" of Zhejiang University(engineering science), 2020, 54(10): 1874-1882.
[23] CHEN S Q, PENG Z K, YANG Y, et al. Intrinsic chirp component decomposition by using Fourier series representation[J]. Signal processing, 2017, 137: 319-327.
OUTPUT POWER PREDICTION OF WAVE POWER SYSTEM BASED ON
VARIATIONAL MODEL DECOMPOSITION AND VECTOR
AUTOREGRESSIVE MODEL
Luo Qi,Yang Junhua,Wang Chaofan,Huang Yi,Liang Haohui
(School of Automation, Guangdong University of Technology, Guangzhou 510006, China)
Abstract:In order to reduce the influence of wave non-smooth characteristics on the energy absorption of direct-drive wave power system, the ridge detection and variational nonlinear chirp mode decomposition is proposed as the control scheme. Using the short-time Fourier transform method to analyze the wave excitation force, the initial frequency is set combined with the ridge detection; using the variational nonlinear chirp mode decomposition method to separate the wave excitation force, obtain several mode components and extract their instantaneous frequencies. Through calculating the energy content of each mode component to determine the dominant component, the damping of the power output device is dynamically adjusted according to its instantaneous frequency to build a model of the direct-drive wave power generation system. Results of the simulation demonstrate that this proposal provides better energy absorption capability and more average power output, thus effectively increasing the power absorption performance of the direct-drive wave power system.
Keywords:wave power system; wave energy conversion; ridge detection; variational nonlinear chirp mode decomposition; power optimization
收稿日期:2022-05-26
基金項(xiàng)目:國(guó)家自然科學(xué)基金(51370265);廣東省教育部產(chǎn)學(xué)研合作專項(xiàng)資金(2013B090500089);廣東省自然科學(xué)基金(2018A030313010);
廣州市科技計(jì)劃(202102021135)
通信作者:楊俊華(1965—),男,博士、教授,主要從事電機(jī)電器及其控制、新能源發(fā)電中的控制技術(shù)方面的研究。yly93@qq.com