本文選題：風(fēng)電場(chǎng) + 動(dòng)態(tài)優(yōu)化　； 參考：《燕山大學(xué)》2014年碩士論文

【摘要】：電力系統(tǒng)有功優(yōu)化通過(guò)對(duì)有功潮流的調(diào)整達(dá)到對(duì)某些目標(biāo)值的優(yōu)化，電力系統(tǒng)的無(wú)功優(yōu)化通過(guò)對(duì)無(wú)功潮流的調(diào)整實(shí)現(xiàn)對(duì)相應(yīng)目標(biāo)值的優(yōu)化。這兩種優(yōu)化對(duì)電力系統(tǒng)的優(yōu)化運(yùn)行都具有重要的意義，但是又都具有片面性。本文對(duì)含風(fēng)電場(chǎng)的電力系統(tǒng)進(jìn)行了動(dòng)態(tài)有功優(yōu)化調(diào)度、動(dòng)態(tài)無(wú)功優(yōu)化調(diào)度、動(dòng)態(tài)有功-無(wú)功綜合優(yōu)化調(diào)度。主要內(nèi)容如下： 給出了含風(fēng)電場(chǎng)的電力系統(tǒng)潮流計(jì)算方法。在對(duì)風(fēng)電場(chǎng)的處理中，考慮了單臺(tái)風(fēng)電機(jī)吸收的無(wú)功功率與有功出力以及機(jī)端電壓的關(guān)系。并且計(jì)及了尾流效應(yīng)與風(fēng)電場(chǎng)布局對(duì)于整個(gè)風(fēng)電場(chǎng)輸出功率的影響。對(duì)基本粒子群算法進(jìn)行改進(jìn)，并給出了針對(duì)動(dòng)態(tài)優(yōu)化問(wèn)題的粒子群求解算法。 在有功優(yōu)化中，首先對(duì)不含風(fēng)電場(chǎng)的電力系統(tǒng)進(jìn)行動(dòng)態(tài)經(jīng)濟(jì)調(diào)度，然后采用模糊處理的方法，建立含風(fēng)電場(chǎng)的電力系統(tǒng)節(jié)能環(huán)保多目標(biāo)模糊模型，對(duì)風(fēng)電出力進(jìn)行模糊處理。針對(duì)多目標(biāo)模型中難以進(jìn)行模糊處理的問(wèn)題，提出對(duì)多目標(biāo)模糊模型的分步處理策略。采用求解Pareto最優(yōu)解集的方法求解此多目標(biāo)優(yōu)化問(wèn)題，對(duì)含風(fēng)電場(chǎng)的電力系統(tǒng)進(jìn)行動(dòng)態(tài)有功優(yōu)化調(diào)度，并仿真驗(yàn)證。 由于無(wú)功優(yōu)化模型中含有離散變量，本文采用針對(duì)含有離散變量的優(yōu)化問(wèn)題的粒子群算法進(jìn)行求解。相對(duì)于靜態(tài)無(wú)功優(yōu)化問(wèn)題，動(dòng)態(tài)無(wú)功優(yōu)化問(wèn)題的難點(diǎn)在于對(duì)控制設(shè)備投切次數(shù)約束的處理，針對(duì)此問(wèn)題采用對(duì)控制設(shè)備動(dòng)作時(shí)刻動(dòng)態(tài)調(diào)整的方法，進(jìn)而對(duì)含風(fēng)電場(chǎng)的電力系統(tǒng)進(jìn)行動(dòng)態(tài)無(wú)功優(yōu)化調(diào)度，并對(duì)此進(jìn)行仿真驗(yàn)證。 針對(duì)單獨(dú)進(jìn)行有功優(yōu)化和無(wú)功優(yōu)化的片面性、不全面性的問(wèn)題，提出有功-無(wú)功綜合優(yōu)化方法。建立了含風(fēng)電場(chǎng)的電力系統(tǒng)有功-無(wú)功多目標(biāo)優(yōu)化數(shù)學(xué)模型，并給出對(duì)有功-無(wú)功多目標(biāo)優(yōu)化模型的求解方法，通過(guò)算例對(duì)此模型進(jìn)行仿真驗(yàn)證。
[Abstract]:The active power optimization of power system achieves the optimization of some target values through the adjustment of the active power flow, and the reactive power optimization of the power system realizes the optimization of the corresponding target value by adjusting the reactive power flow. These two kinds of optimization are of great significance to the optimal operation of power system, but both have one-sidedness. In this paper, dynamic active power optimal scheduling, dynamic reactive power optimal scheduling and dynamic active and reactive power comprehensive optimal scheduling are carried out for the power system with wind farm. The main contents are as follows: The power flow calculation method of power system with wind farm is presented. In the treatment of wind farm, the relationship between reactive power absorbed by single typhoon motor and active power output as well as terminal voltage is considered. The effects of wake effect and wind farm layout on the output power of the wind farm are also taken into account. The basic particle swarm optimization algorithm is improved, and the particle swarm optimization algorithm for dynamic optimization problem is presented. In the active power optimization, the dynamic economic dispatch of the power system without wind farm is first carried out, and then the fuzzy processing method is adopted to establish the multi-objective fuzzy model of energy saving and environmental protection of the power system with wind farm, and the fuzzy treatment of wind power output is carried out. Aiming at the difficulty of fuzzy processing in multi-objective model, a step by step strategy for multi-objective fuzzy model is proposed. The multi-objective optimization problem is solved by solving the Pareto optimal solution set. The dynamic active power optimal scheduling of the power system with wind farm is carried out and verified by simulation. Because the reactive power optimization model contains discrete variables, particle swarm optimization (PSO) algorithm is used to solve the optimization problem with discrete variables. Compared with the static reactive power optimization problem, the difficulty of the dynamic reactive power optimization problem is to deal with the control equipment switching times constraint. Then the dynamic reactive power optimal dispatching of the power system with wind farm is carried out, and the simulation is carried out. Aiming at the one-sidedness and incompleteness of active power optimization and reactive power optimization, a comprehensive method of active and reactive power optimization is proposed. The mathematical model of active and reactive power multi-objective optimization of power system with wind farm is established, and the method of solving the multi-objective optimization model of active and reactive power is given. The simulation results of the model are verified by an example.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TM614;TM73

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