Suzhou Electric Appliance Research Institute
期刊號(hào): CN32-1800/TM| ISSN1007-3175

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含風(fēng)電場(chǎng)的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度

來(lái)源:電工電氣發(fā)布時(shí)間:2019-08-16 13:16 瀏覽次數(shù):660
含風(fēng)電場(chǎng)的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度
 
麻利新,翟帥華,李萍
(寧夏大學(xué) 物理與電子電氣工程學(xué)院,寧夏 銀川 750021)
 
    摘 要:針對(duì)火力發(fā)電對(duì)環(huán)境造成的嚴(yán)重污染問(wèn)題,建立了含風(fēng)電場(chǎng)的電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度模型。以火電機(jī)組燃料費(fèi)用和污染氣體排放量最低為目標(biāo),用虛擬解理論將多目標(biāo)優(yōu)化問(wèn)題轉(zhuǎn)化為單目標(biāo)優(yōu)化問(wèn)題,以降低問(wèn)題的復(fù)雜性;用動(dòng)態(tài)搜索步長(zhǎng)及動(dòng)態(tài)搜索概率對(duì)布谷鳥(niǎo)算法改進(jìn),用改進(jìn)后的算法求解所建立調(diào)度模型。仿真結(jié)果表明,改進(jìn)算法在符合有功平衡約束、機(jī)組出力約束及機(jī)組爬坡約束等同樣的前提條件下,具有節(jié)約發(fā)電成本,減少污染物排放,加快系統(tǒng)運(yùn)行速度的優(yōu)點(diǎn)。
    關(guān)鍵詞:風(fēng)電場(chǎng);污染物排放;多目標(biāo)優(yōu)化;虛擬解;布谷鳥(niǎo)算法
    中圖分類(lèi)號(hào):TM614     文獻(xiàn)標(biāo)識(shí)碼:A     文章編號(hào):1007-3175(2019)08-0007-04
 
Multi-Objective Optimal Scheduling of Power System Including Wind Farm
 
MA Li-xin, ZHAI Shuai-hua, LI Ping
(School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China)
 
    Abstract: Aiming at the serious pollution problem caused by thermal power generation, this paper established a multi-objective optimization scheduling model of power system including wind farms. In order to reduce the complexity of the problem, the multi-objective optimization problem was transformed into a single-objective optimization problem by using the virtual solution theory, aiming at the lowest fuel cost and the lowest emission of polluted gases. The cuckoo algorithm was improved by using dynamic search step size and dynamic search probability, and the improved algorithm was used for solving the established scheduling model. The simulation results show that the improved algorithm has the advantages of saving power generation costs, reducing pollutant emissions and speeding up the system operation under the same preconditions as active power balance constraints, unit output constraints and unit climbing constraints and so on.
    Key words: wind farm; pollutant emissions; multi-objective optimization; virtual solution; cuckoo algorithm
 
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