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含風電場的電力系統(tǒng)多目標無功優(yōu)化

發(fā)布時間:2018-04-13 03:10

  本文選題:多目標無功優(yōu)化 + 風電場。 參考:《中國礦業(yè)大學》2017年碩士論文


【摘要】:隨著經濟的發(fā)展,我國的能源安全和環(huán)境問題已不容忽視,風能作為一種可再生、無污染的綠色能源,給電力行業(yè)的發(fā)展帶了無限前景。根據(jù)國家能源局發(fā)布的《風電發(fā)展“十三五”規(guī)劃》,“十三五”期間風電投資規(guī)模將達7000億以上。由于風能的隨機性、波動性和間歇性,風電的大規(guī)模開發(fā)和利用必將對電力系統(tǒng)的潮流產生較大影響。因此,分析含風電場的電力系統(tǒng)潮流計算方法,研究電力系統(tǒng)多目標無功優(yōu)化算法,確定大容量風場接入系統(tǒng)的無功優(yōu)化策略,對于提高風能利用率、改善電壓質量以及保證系統(tǒng)運行穩(wěn)定性都具有重要的意義。本文在研究了含風電場電力系統(tǒng)潮流計算方法的基礎上,采用PSO-NSGA-II算法對含風電場的電力系統(tǒng)進行多目標無功優(yōu)化。首先,研究了基于牛頓-拉夫遜法和QV聯(lián)合迭代模型的含風電場電力系統(tǒng)潮流計算方法。本文探討了電力系統(tǒng)潮流計算幾種常用方法的迭代思想,在建立了異步風力發(fā)電機組的數(shù)學模型和輸出功率模型之后,著重分析了風電場并網(wǎng)節(jié)點的處理方法。其次,采用基于Pareto的多目標優(yōu)化方法,同時考慮有功網(wǎng)損、節(jié)點電壓偏移量和靜態(tài)電壓穩(wěn)定裕度多個目標函數(shù),研究了電力系統(tǒng)多目標無功優(yōu)化方法。無功優(yōu)化問題屬于多目標的非線性規(guī)劃問題,基于Pareto的優(yōu)化方法能夠綜合考慮各個目標的情況,求得更合適的優(yōu)化方案。再次,結合控制變量既有離散變量又有連續(xù)變量的特點,針對帶精英策略的非支配排序遺傳算法在離散空間收斂快的優(yōu)點,引入在連續(xù)空間收斂快的粒子群算法思想,提出了更適用于無功優(yōu)化問題的PSO-NSGA-II算法,并利用約束違反度的概念求解有約束優(yōu)化問題。最后,通過接入風電場的IEEE-14節(jié)點系統(tǒng)算例仿真,驗證風電場潮流計算方法的正確性和PSO-NSGA-II算法的有效性。通過風電場并網(wǎng)節(jié)點的模型對比,驗證所選QV聯(lián)合迭代模型能夠兼顧計算速度和準確性。通過與NSGA-II算法進行評價指標的對比,證明PSO-NSGA-II算法能夠有效地處理多目標優(yōu)化問題,且具有更好的全局收斂性能。
[Abstract]:With the development of economy, the problems of energy security and environment in our country can not be ignored. Wind energy, as a kind of renewable and pollution-free green energy, brings an infinite prospect to the development of electric power industry.According to the 13th Five-Year Plan of Wind Power Development issued by the State Energy Administration, the scale of wind power investment will reach more than 700 billion during the 13th Five-Year Plan period.Due to the randomness, volatility and intermittency of wind energy, the large-scale development and utilization of wind power will have a great impact on the power flow of power system.Therefore, the power flow calculation method with wind farm is analyzed, the multi-objective reactive power optimization algorithm is studied, and the reactive power optimization strategy for large capacity wind field access system is determined, which can improve the utilization rate of wind energy.It is very important to improve the voltage quality and ensure the stability of the system.Based on the study of the power flow calculation method of the power system with wind farm, the PSO-NSGA-II algorithm is used to optimize the reactive power of the power system with wind farm.Firstly, the power flow calculation method of power system with wind farm is studied based on Newton-Raphson method and QV combined iteration model.In this paper, the iterative idea of several common methods for power flow calculation is discussed. After the mathematical model and output power model of asynchronous wind turbine are established, the processing method of connected nodes of wind farm is analyzed emphatically.Secondly, the multi-objective reactive power optimization method based on Pareto is studied by taking into account the active power network loss, node voltage offset and static voltage stability margin.Reactive power optimization is a multi-objective nonlinear programming problem. The optimization method based on Pareto can comprehensively consider the situation of each objective and obtain a more suitable optimization scheme.Thirdly, considering the characteristics that control variables have both discrete variables and continuous variables, aiming at the advantage of fast convergence in discrete space of non-dominated sorting genetic algorithm with elite strategy, the idea of particle swarm optimization (PSO) with fast convergence in continuous space is introduced.A new PSO-NSGA-II algorithm for reactive power optimization is proposed, and the concept of constraint violation is used to solve the constrained optimization problem.Finally, the correctness of the wind farm power flow calculation method and the validity of the PSO-NSGA-II algorithm are verified by the simulation of the IEEE-14 node system connected with the wind farm.By comparing the models of grid connected nodes of wind farm, it is verified that the QV joint iterative model can take into account the calculation speed and accuracy.By comparing with the evaluation index of NSGA-II algorithm, it is proved that the PSO-NSGA-II algorithm can deal with the multi-objective optimization problem effectively and has better global convergence performance.
【學位授予單位】:中國礦業(yè)大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TM614;TM714.3

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