【摘要】：電力系統(tǒng)建模是對其分析、計(jì)算、控制的基礎(chǔ)。由于系統(tǒng)運(yùn)行狀態(tài)多變及參數(shù)的不確定性,進(jìn)行電力系統(tǒng)精確建模非常困難。另一方面,現(xiàn)代電力系統(tǒng)是非線性、高維度、大規(guī)模的動態(tài)系統(tǒng),對其采用恰當(dāng)有效的控制是保障電力系統(tǒng)安全穩(wěn)定運(yùn)行的關(guān)鍵�，F(xiàn)有的電力系統(tǒng)控制器往往基于某一個運(yùn)行點(diǎn)設(shè)計(jì),難以保障在系統(tǒng)各種復(fù)雜運(yùn)行工況下保持好的控制效果,甚至不能保持系統(tǒng)穩(wěn)定。多層次啟發(fā)式動態(tài)規(guī)劃具有很強(qiáng)的自適應(yīng)性,通過離線訓(xùn)練和在線修正,逐漸學(xué)習(xí)并掌握系統(tǒng)的動態(tài)特性,在模型未知和參數(shù)不確定的情況下,能夠進(jìn)行電力系統(tǒng)建模和控制。本文將多層次啟發(fā)式動態(tài)規(guī)劃用于電力系統(tǒng)建模和控制,主要研究內(nèi)容如下:在啟發(fā)式動態(tài)規(guī)劃(Heuristic Dynamic Programming,HDP)的基礎(chǔ)上,深入地研究多層次啟發(fā)式動態(tài)規(guī)劃(Goal representative Heuristic Dynamic Programming,GrHDP)算法。以倒立擺系統(tǒng)為例進(jìn)行仿真研究,結(jié)果表明:基于GrHDP設(shè)計(jì)的控制器比基于HDP設(shè)計(jì)的控制器對最優(yōu)目標(biāo)的跟蹤更迅速,穩(wěn)定速度更快,控制效果也更加精確。針對目前風(fēng)電場并網(wǎng)點(diǎn)處靜止無功補(bǔ)償器(Static Var Compensator,SVC)裝置控制系統(tǒng)帶來的高電壓穿越問題,提出了基于GrHDP的SVC電壓無功控制策略。以4機(jī)2區(qū)域系統(tǒng)為例進(jìn)行仿真研究,結(jié)果表明:在不同的運(yùn)行工況和故障情況下,與采用粒子群優(yōu)化算法設(shè)計(jì)的PID型SVC電壓無功控制器相比,本文所提的基于GrHDP的電壓無功控制器都能更有效抑制故障后風(fēng)電場并網(wǎng)點(diǎn)的過電壓。針對電力系統(tǒng)運(yùn)行工況變化后動態(tài)等值系統(tǒng)響應(yīng)不夠精確的問題,提出了基于GrHDP的電力系統(tǒng)動態(tài)等值算法。以10機(jī)39節(jié)點(diǎn)系統(tǒng)為例進(jìn)行仿真研究,結(jié)果表明:在不同運(yùn)行工況和故障方式下,相比于同調(diào)等值法,本文提出的基于GrHDP的電力系統(tǒng)動態(tài)等值算法都能更精確地跟蹤原系統(tǒng)的動態(tài)特性。
[Abstract]:Power system modeling is the basis of its analysis, calculation and control. The accurate modeling of power system is very difficult because of the variable operation state and uncertainty of parameters. On the other hand, modern power system is a nonlinear, high-dimensional, large-scale dynamic system. Proper and effective control is the key to ensure the safe and stable operation of power system. The existing power system controllers are often designed on the basis of a certain operating point, which is difficult to guarantee the good control effect under various complex operating conditions of the system, or even to maintain the stability of the system. Multi-level heuristic dynamic programming has strong adaptability. Through off-line training and on-line modification, the dynamic characteristics of the system can be gradually learned and mastered, and the power system modeling and control can be carried out under the condition of unknown model and uncertain parameters. In this paper, multi-level heuristic dynamic programming is applied to power system modeling and control. The main research contents are as follows: on the basis of heuristic dynamic programming (Heuristic Dynamic Programming,HDP), the multi-level heuristic dynamic programming (Goal representative Heuristic Dynamic Programming,) is deeply studied. GrHDP) algorithm. Taking inverted pendulum system as an example, the simulation results show that the controller based on GrHDP can track the optimal target more quickly, the stability speed is faster and the control effect is more accurate than the controller based on HDP. Aiming at the problem of high voltage traversing caused by the control system of static Var compensator (Static Var Compensator,SVC) at the point of wind farm, a SVC voltage and reactive power control strategy based on GrHDP is proposed. The simulation of 4-machine 2 area system is carried out. The results show that under different operating conditions and fault conditions, compared with PID type SVC voltage and reactive power controller designed by particle swarm optimization algorithm, The voltage and reactive power controller proposed in this paper based on GrHDP can restrain the overvoltage of wind farm after fault more effectively. A dynamic equivalent algorithm based on GrHDP is proposed to solve the problem that the dynamic equivalent system response is not accurate enough after the change of power system operating conditions. The simulation of a 10-machine 39-bus system is carried out. The results show that under different operating conditions and fault modes, compared with the homology equivalent method, The power system dynamic equivalence algorithm based on GrHDP proposed in this paper can track the dynamic characteristics of the original system more accurately.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TM732

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本文編號：2310488