基于多層次自適應動態(tài)規(guī)劃的電力系統建模與控制
發(fā)布時間：2018-11-04 16:44
【摘要】：電力系統建模是對其分析、計算、控制的基礎。由于系統運行狀態(tài)多變及參數的不確定性,進行電力系統精確建模非常困難。另一方面,現代電力系統是非線性、高維度、大規(guī)模的動態(tài)系統,對其采用恰當有效的控制是保障電力系統安全穩(wěn)定運行的關鍵�，F有的電力系統控制器往往基于某一個運行點設計,難以保障在系統各種復雜運行工況下保持好的控制效果,甚至不能保持系統穩(wěn)定。多層次啟發(fā)式動態(tài)規(guī)劃具有很強的自適應性,通過離線訓練和在線修正,逐漸學習并掌握系統的動態(tài)特性,在模型未知和參數不確定的情況下,能夠進行電力系統建模和控制。本文將多層次啟發(fā)式動態(tài)規(guī)劃用于電力系統建模和控制,主要研究內容如下:在啟發(fā)式動態(tài)規(guī)劃(Heuristic Dynamic Programming,HDP)的基礎上,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。以倒立擺系統為例進行仿真研究,結果表明:基于GrHDP設計的控制器比基于HDP設計的控制器對最優(yōu)目標的跟蹤更迅速,穩(wěn)定速度更快,控制效果也更加精確。針對目前風電場并網點處靜止無功補償器(Static Var Compensator,SVC)裝置控制系統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2區(qū)域系統為例進行仿真研究,結果表明:在不同的運行工況和故障情況下,與采用粒子群優(yōu)化算法設計的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電場并網點的過電壓。針對電力系統運行工況變化后動態(tài)等值系統響應不夠精確的問題,提出了基于GrHDP的電力系統動態(tài)等值算法。以10機39節(jié)點系統為例進行仿真研究,結果表明:在不同運行工況和故障方式下,相比于同調等值法,本文提出的基于GrHDP的電力系統動態(tài)等值算法都能更精確地跟蹤原系統的動態(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.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM732
本文編號：2310488
[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.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM732
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，本文編號：2310488
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