改進黑洞粒子群算法在電力系統(tǒng)環(huán)保經(jīng)濟調(diào)度中的應用 

宗超凡，代奇跡，趙海麗 
(貴州大學 電氣工程學院，貴州 貴陽 550000) 
 

摘 要： 針對電力系統(tǒng)中的環(huán)保經(jīng)濟調(diào)度問題，采用了一種改進隨機黑洞粒子群算法進行優(yōu)化計算。該算法通過引入隨機黑洞策略、慣性權重和學習因子動態(tài)更新及小概率隨機變異改進了粒子群算法，提高了全局搜索能力，穩(wěn)定了計算結(jié)果，加快了收斂速度。通過對IEEE30 系統(tǒng)仿真計算，結(jié)果驗證了該算法的有效性和優(yōu)越性，系統(tǒng)的經(jīng)濟性和電能質(zhì)量都得到了提升。
關鍵詞： 隨機黑洞策略；動態(tài)更新技術；小概率隨機變異；環(huán)保經(jīng)濟調(diào)度
中圖分類號：TM744 文獻標識碼：A 文章編號：1007-3175(2016)01-0033-04

Application of Improved Black Hole Particle Swarm Optimization Algorithm in Environmental Economic Dispatch of Power System 

ZONG Chao-fan, DAI Qi-ji, ZHAO Hai-li 
（The Electrical Engineering College, Guizhou University, Guiyang 550000, China） 
 

Abstract: In allusion to the problem of environmental economic dispatch in power system, this paper proposed a kind of improved random black particle swarm optimization algorithm to carry out optimal computation. This paper introduced random black hole strategy,dynamic updates of inertia weight and learning factor, small probability random mutation to improve the particle swarm optimization algorithm and raised the global searching ability, stability of the results and acceleration of the convergence rate. The proposed algorithm is used to calculate the environmental economic dispatch in IEEE30 system. The simulation results show the effectiveness and superiority of this algorithm, and the power system has more economical efficiency and better power quality.
Key words: random black hole strategy; dynamic updating technology; small probability random mutation; environmental economic dispatch

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