基于概率潮流的機會約束規(guī)劃方法及求解
管永麗
(東南大學(xué) 電氣工程學(xué)院,江蘇 南京 210096)
摘 要: 為了解決傳統(tǒng)的輸電系統(tǒng)面對發(fā)電、輸電以及負(fù)荷的不確定因素的增加無法提出可靠的規(guī)劃方案的問題,提出了基于概率潮流的機會約束規(guī)劃方法,綜合考慮節(jié)點負(fù)荷值、發(fā)電機出力等不確定性因素,是一類隨機優(yōu)化方法。給出了基于蒙特卡洛仿真的驗證方法和基于遺傳算法的求解方法,并以一個簡單算例驗證了該方法的可行性。
關(guān)鍵詞: 遺傳算法;概率潮流;分布式電源;機會約束規(guī)劃;半不變量法
中圖分類號:TM715 文獻標(biāo)識碼:A 文章編號:1007-3175(2016)01-0017-04
Chance-Constrained Programming Methods Based on Probabilistic Load Flow
GUAN Yong-li
(School of Electrical Engineering, Southeast University, Nanjing 210096, China)
Abstract: In order to solve the problem that for the traditional power transmission system, it isn’t able to give reliable planning schemes to face the increase of uncertainties such as power generation, power transmission and load. This paper proposed a chance-constrained programming method based on probabilistic load flow, in overall consideration of uncertainty factors such as node load values, the generator output. This is a kind of stochastic optimization method. This paper gave the verification method based on Monte Carlo simulation and the solving method based on genetic algorithm. A simple numerical example illustrates the feasibility of this method.
Key words: genetic algorithm; probabilistic load flow; distributed power; chance-constrained programming; half invariant method
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