需要金幣： 1000 個(gè)金幣 |
資料包括：完整論文 |  |
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| 轉(zhuǎn)換比率：金額 X 10=金幣數(shù)量， 例100元=1000金幣 | 論文字?jǐn)?shù)：18331 |  | |
| 折扣與優(yōu)惠：團(tuán)購(gòu)最低可5折優(yōu)惠 - 了解詳情 | 論文格式：Word格式(*.doc) |  |
摘要：現(xiàn)代社會(huì)的發(fā)展離不開(kāi)電力的支持，人們對(duì)電力工業(yè)的依賴越來(lái)越強(qiáng)。即使我國(guó)的裝機(jī)容量與日俱增，仍滿足不了人們?nèi)找嬖鲩L(zhǎng)的電力需求。同時(shí)人們對(duì)電能質(zhì)量的關(guān)注度越來(lái)越高。電力系統(tǒng)的無(wú)功優(yōu)化作為節(jié)能降損和提高電能質(zhì)量的重要手段之一，受到越來(lái)越多的研究人員的重視。本文分析了無(wú)功補(bǔ)償改善電壓質(zhì)量和降低損耗的原理，采用遺傳算法確定無(wú)功補(bǔ)償接入點(diǎn)和其補(bǔ)償容量。本文對(duì)一般遺傳算法作了一些改進(jìn)，提高了算法的運(yùn)算速度和全局尋優(yōu)能力。 本文利用matlab軟件對(duì)IEEE33節(jié)點(diǎn)系統(tǒng)進(jìn)行了仿真測(cè)試，從優(yōu)化結(jié)果上看，遺傳算法能切實(shí)解決無(wú)功優(yōu)化問(wèn)題，有效減少電網(wǎng)有功損耗和提高節(jié)點(diǎn)電壓質(zhì)量,具有良好的應(yīng)用前景。 關(guān)鍵詞：無(wú)功優(yōu)化；遺傳算法；電壓質(zhì)量；有功網(wǎng)損
ABSTRACT：Electric power, with people’s increasing dependence on electric industry, plays a crucial role in the sustainable development of modern society. Though the installed capacity of power system of China has been enlarging massively during the past decades, it still lags behind the growing demand of this huge society. Simultaneously, individuals are paying closer attention to the electric quality. As an effective technique to improve voltage quality and lessen power loss, reactive power optimization (RPO) is always a hotspot for electric researchers. this paper analyze the function of reactive compensation. We utilize Genetic Algorithm to fix compensation locations and their corresponding compensation capacity. We introduce some methods to improve GA for quicker convergence and better global search ability. Simulation results, in matlab environment, of IEEE 33-bus system show that GA can solve the RPO problem cogently. GA has a promising prospect of practical application. KEYWORDS: Reactive Power Optimization; Genetic Algorithm; Voltage Quality; Power Loss |
