【摘要】：可再生能源是世界各國(guó)未來(lái)經(jīng)濟(jì)與能源利用發(fā)展的重要方向。微電網(wǎng)不僅能并網(wǎng)運(yùn)行,而且也可以作為獨(dú)立電網(wǎng)運(yùn)行,在部分山區(qū)和海島等偏遠(yuǎn)孤立地帶,微電網(wǎng)不僅能夠解決當(dāng)?shù)毓╇妴?wèn)題,而且可以減少大量供電設(shè)施建設(shè)的成本,改善偏遠(yuǎn)地區(qū)的生產(chǎn)生活水平。其中風(fēng)力、光伏及儲(chǔ)能電池組成的風(fēng)光互補(bǔ)系統(tǒng)是眾多新能源示范項(xiàng)目的主要構(gòu)成形式,本文以其為研究對(duì)象,主要研究工作有:(1)多目標(biāo)差分進(jìn)化算法的改進(jìn)研究。為了避免算法陷入局部最優(yōu),增加其收斂速度,更好地模擬生物自然進(jìn)化過(guò)程,在原有的基于分解的多目標(biāo)進(jìn)化算法(MOEA/D)的基礎(chǔ)上,將混沌初值理論、參數(shù)自適應(yīng)方法和線(xiàn)性加權(quán)和的方法引入該算法,通過(guò)測(cè)試函數(shù)的測(cè)試初步達(dá)到了改進(jìn)的效果。(2)獨(dú)立型風(fēng)光互補(bǔ)系統(tǒng)中分布式電源經(jīng)濟(jì)性和可靠性容量配置的研究。本部分分別分析系統(tǒng)的光伏電源、風(fēng)力發(fā)電機(jī)和蓄電池的工作特性,建立系統(tǒng)的經(jīng)濟(jì)性和可靠性目標(biāo),進(jìn)行IMOEA/D的微源容量配置優(yōu)化的研究,并與其他常用多目標(biāo)進(jìn)化算法(SPEA、NSGA-Ⅱ、MOPSO、NNIA)的優(yōu)化結(jié)果進(jìn)行比較,得出符合工程需要的微網(wǎng)系統(tǒng)分布式電源容量?jī)?yōu)化配置組合。(3)獨(dú)立型風(fēng)光互補(bǔ)系統(tǒng)分布式電源能量控制的MATLAB/Simulink仿真研究。在最大限度利用可再生能源的原則下,先后做出了光伏電源和風(fēng)力發(fā)電機(jī)的變步長(zhǎng)爬山法最大功率的跟蹤(MPPT)仿真模型以及蓄電池的恒壓充放電的能量控制模型,提高微網(wǎng)系統(tǒng)的可再生能源的利用率和穩(wěn)定性。將本文提出的IMOEA/D應(yīng)用到實(shí)際工程中,在可靠性近似相等的情況下,IMOEA/D獲得經(jīng)濟(jì)成本均小于其它算法獲得的結(jié)果;而對(duì)于本文提出的變步長(zhǎng)爬山法跟蹤結(jié)果,其跟蹤時(shí)間和跟蹤過(guò)程中產(chǎn)生的波動(dòng)都比傳統(tǒng)的定步長(zhǎng)的要小,可以提高跟蹤效率和穩(wěn)定性;最后對(duì)蓄電池的控制技術(shù)可以是其輸出電壓穩(wěn)定在理想電壓范圍內(nèi),并且可以實(shí)現(xiàn)充放電模式的轉(zhuǎn)換和控制。
[Abstract]:Renewable energy is an important direction of economic and energy utilization in the world. Microgrid not only can be connected to the grid, but also can be operated as an independent grid. In some remote and isolated areas such as mountainous areas and islands, microgrid can not only solve the local power supply problem, but also reduce the construction cost of a large number of power supply facilities. Improve production and living standards in remote areas. Wind, photovoltaic and solar energy storage cells are the main components of many new energy demonstration projects. In this paper, the main research work is as follows: (1) the improvement of multi-objective differential evolution algorithm. In order to avoid the algorithm falling into local optimum, increase its convergence speed, and better simulate the natural evolution process of biology, the chaotic initial value theory is based on the original decomposition-based multiobjective evolutionary algorithm (MOEA/D). The parameter adaptive method and the linear weighted sum method are introduced, and the improved results are obtained by testing the test function. (2) the research on the economy and reliability capacity configuration of distributed power supply in the independent wind and wind complementary system. In this part, the characteristics of photovoltaic power supply, wind turbine and battery are analyzed respectively, and the economic and reliability targets of the system are established, and the optimization of IMOEA/D micro-source capacity configuration is studied. The results are compared with those of other commonly used multi-objective evolutionary algorithms (SPEA,NSGA- 鈪，

本文編號(hào)：2220152