本文選題：風(fēng)電機組 + 變槳距控制�。� 參考：《中北大學(xué)》2017年碩士論文

【摘要】：目前,風(fēng)力發(fā)電技術(shù)日趨成熟,變槳距控制系統(tǒng)在大中型風(fēng)電機組中得到了廣泛應(yīng)用。然而,由于風(fēng)能的隨機性以及風(fēng)力機變槳距系統(tǒng)的復(fù)雜非線性,風(fēng)速變化會導(dǎo)致風(fēng)電機組輸出功率產(chǎn)生波動而無法穩(wěn)定于額定功率處,如何獲得較高的風(fēng)能捕獲率以及平穩(wěn)的輸出功率是風(fēng)電技術(shù)的研究重點之一。論文首先介紹了變槳距技術(shù)的工作原理,對風(fēng)電變槳距系統(tǒng)的各個組成部分進行數(shù)學(xué)建模和Matlab仿真,并基于系統(tǒng)的非線性特性以及具有未知擾動的特點,設(shè)計了風(fēng)力機變槳距自抗擾控制器(Active Disturbance Rejection Control Technique,ADRC)。其次,針對ADRC參數(shù)多且難以整定的缺點,論文采用混沌粒子群算法對其進行優(yōu)化,實現(xiàn)ADRC參數(shù)的自尋優(yōu)整定。再次,在ADRC中,當外界擾動過大時擴展狀態(tài)觀測器的估計能力會有所降低,論文將可以通過系統(tǒng)辨識得到的已知擾動部分前饋補償于ESO中以減少其需要估計的擾動。另外,文中采用fhan函數(shù)實現(xiàn)了微分跟蹤器及非線性反饋控制律兩部分的無參數(shù)整定。最后,通過將文中提出的兩種優(yōu)化ADRC與傳統(tǒng)ADRC進行仿真比較,驗證了設(shè)計的可行性及有效性。本文提出的基于混沌粒子群優(yōu)化算法的ADRC與基于模型補償?shù)腁DRC算法簡單,可實現(xiàn)性強,利用優(yōu)化的ADRC對變槳距系統(tǒng)進行控制,可以有效提高風(fēng)電機組輸出功率的效率以及穩(wěn)定性。
[Abstract]:At present, wind power generation technology is becoming more and more mature, variable pitch control system has been widely used in large and medium-sized wind turbines. However, because of the randomness of wind energy and the complexity and nonlinearity of wind turbine pitch system, the variation of wind speed will lead to the fluctuation of output power of wind turbine, which can not be stabilized at the rated power. How to obtain high wind energy capture rate and steady output power is one of the key points in wind power technology. This paper first introduces the working principle of variable pitch technology, and carries on mathematical modeling and Matlab simulation of each component of wind power variable pitch system, and based on the nonlinear characteristics of the system and the characteristics of unknown disturbance. An active Disturbance Rejection Control technique controller for wind turbine pitch rejection is designed. Secondly, aiming at the disadvantage that ADRC parameters are many and difficult to adjust, chaotic particle swarm optimization algorithm is used to optimize ADRC parameters. Thirdly, in ADRC, when the external disturbance is too large, the estimation ability of the extended state observer will be reduced, and the known disturbance partial feedforward can be compensated by the system identification in ESO to reduce the disturbance that needs to be estimated. In addition, the fhan function is used to realize the parameterless tuning of the differential tracker and the nonlinear feedback control law. Finally, the feasibility and effectiveness of the design are verified by comparing the two optimized ADRC proposed in this paper with the traditional ADRC. The proposed ADRC algorithm based on chaotic particle swarm optimization and ADRC algorithm based on model compensation are simple and realizable. The optimized ADRC is used to control the variable pitch system. It can effectively improve the efficiency and stability of wind turbine output power.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP273;TM315

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