【摘要】：微電網(wǎng)是促進分布式電源大規(guī)模應用的有效途徑之一。微電網(wǎng)運行經(jīng)濟性的提高能夠為其未來的發(fā)展和推廣奠定基礎。微電網(wǎng)經(jīng)濟運行研究當中,通過分布式電源選址定容優(yōu)化能夠降低線路的損耗,然而現(xiàn)有研究的側重點主要是分析對配電網(wǎng)網(wǎng)損的影響,對微電網(wǎng)內部網(wǎng)損影響的研究并不完善；另外,傳統(tǒng)基于集中控制的儲能優(yōu)化方法隨著微電網(wǎng)規(guī)模的擴大控制難度也會逐漸增加,有一定的局限性,而分散控制則能滿足微電網(wǎng)未來發(fā)展的需求。因此,本論文將針對上述兩個方面展開研究。 首先,本論文分析了光伏發(fā)電系統(tǒng)、蓄電池系統(tǒng)以及微電網(wǎng)線路損耗的數(shù)學模型,并構建了光伏發(fā)電系統(tǒng)和蓄電池系統(tǒng)的SIMULINK仿真模型。驗證了光伏系統(tǒng)基于占空比擾動觀察法的最大功率跟蹤控制方法和蓄電池恒母線電壓充放電策略的有效性。 其次,結合本論文分析的微電網(wǎng)線路損耗模型與求解目標、約束條件等構建了分布式電源選址定容優(yōu)化的數(shù)學模型。運用免疫算法對模型進行求解,并編寫程序在MATLAB中進行了仿真驗證。 最后,運用小波神經(jīng)網(wǎng)絡算法對微電網(wǎng)中分布式電源發(fā)電值以及系統(tǒng)負載值進行短期預測,在此基礎上建立了一種基于蓄電池荷電狀態(tài)、實時電價、分布式電源當前發(fā)電和負載功率以及未來短期發(fā)電負載預測功率的模糊控制策略,并通過SIMULINK進行了仿真驗證。 研究結果表明,本文設計的基于免疫算法的分布式電源選址定容優(yōu)化方法與基于模糊控制的儲能系統(tǒng)充放電優(yōu)化算法可提高微電網(wǎng)運行的經(jīng)濟性。其中,分布式電源經(jīng)選址定容優(yōu)化之后能夠使微電網(wǎng)內部線路總長度降低58.9%,總網(wǎng)損由3.9%下降至0.539%；儲能系統(tǒng)充放電優(yōu)化后能夠利用實時電價創(chuàng)造額外9.8%的經(jīng)濟效益。論文的相關研究結果對微電網(wǎng)的經(jīng)濟運行具有一定的理論價值和工程應用價值。
[Abstract]:Microgrid is one of the effective ways to promote the large-scale application of distributed generation. The improvement of microgrid operation economy can lay a foundation for its future development and promotion. In the research of economic operation of microgrid, the loss of transmission line can be reduced by optimizing the location and capacity of distributed generation. However, the emphasis of the present research is to analyze the influence on the network loss of distribution network. The research on the influence of internal network loss on microgrid is not perfect. In addition, the traditional energy storage optimization method based on centralized control will gradually increase the difficulty of microgrid control with the expansion of the scale, and has some limitations, while decentralized control can meet the needs of the future development of microgrid. Therefore, this thesis will focus on the above two aspects. Firstly, this paper analyzes the mathematical models of photovoltaic power generation system, battery system and microgrid line loss, and constructs the SIMULINK simulation model of photovoltaic power system and battery system. The effectiveness of the maximum power tracking control method based on the duty cycle perturbation observation method and the charging and discharging strategy of battery constant bus voltage are verified. Secondly, the mathematical model of distributed power source location and capacity optimization is constructed by combining the line loss model and solving target, constraint condition and so on of the microgrid analyzed in this paper. The immune algorithm is used to solve the model, and a program is written for simulation in MATLAB. Finally, the wavelet neural network algorithm is used to predict the generation value and system load value of distributed generation in microgrid, and a real-time electricity price based on the charging state of battery is established. The fuzzy control strategy for the current generation and load power of distributed power generation and the predicted power of future short-term generation load is verified by SIMULINK simulation. The results show that the immune algorithm based on the immune algorithm and the fuzzy control algorithm can improve the economy of micro-grid operation. The total length of the microgrid line can be reduced by 58.9 and the total network loss can be reduced from 3.9% to 0.539% after the distributed power generation is optimized by location and volume. After charging and discharging optimization, the energy storage system can make use of the real-time electricity price to create an extra 9. 8% economic benefit. The research results of this paper have certain theoretical value and engineering application value to the economic operation of microgrid.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM732

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