發(fā)布時(shí)間：2018-04-27 07:45

  本文選題：火電廠 + 負(fù)荷優(yōu)化分配��； 參考：《熱力發(fā)電》2014年12期

【摘要】：在傳統(tǒng)的火電廠經(jīng)濟(jì)負(fù)荷分配模型基礎(chǔ)上,綜合考慮全廠供電煤耗率、污染物排放量以及全廠負(fù)荷升、降時(shí)間3個(gè)目標(biāo),構(gòu)建了廠級(jí)負(fù)荷優(yōu)化分配的多目標(biāo)模型。將差分粒子群混合算法發(fā)展為一種新型的多目標(biāo)進(jìn)化(MDPA)算法,即利用擂臺(tái)賽法和凝聚層次聚類(lèi)分析方法分別構(gòu)造和修剪非支配集,同時(shí)加入精英保留策略,保留進(jìn)化過(guò)程中的極值點(diǎn)。將該算法應(yīng)用于以經(jīng)濟(jì)、環(huán)保、快速3個(gè)目標(biāo)為多目標(biāo)的廠級(jí)負(fù)荷優(yōu)化分配,并與基于非支配排序的多目標(biāo)優(yōu)化(NSGA-Ⅱ)算法進(jìn)行對(duì)比。結(jié)果表明,MDPA算法較NSGA-Ⅱ算法收斂速度更快,解集分布更均勻。
[Abstract]:On the basis of the traditional economic load distribution model of thermal power plant, a multi-objective model for optimal load distribution of power plant was constructed by considering three objectives: coal consumption rate of power supply, pollutant emission and load increase and drop time of the whole plant. The differential particle swarm optimization (DPSO) hybrid algorithm is developed into a new multi-objective evolutionary MDPA algorithm, in which the non-dominated sets are constructed and pruned by using the beating table method and the condensed hierarchical cluster analysis method, and the elite retention strategy is added. Preserve the extremum of evolution. The proposed algorithm is applied to plant load optimal allocation with three objectives of economy, environmental protection and speed, and is compared with the NSGA- 鈪，

本文編號(hào)：1809870