【摘要】：將微電網(wǎng)運(yùn)行的經(jīng)濟(jì)性和環(huán)保性作為目標(biāo)進(jìn)行優(yōu)化調(diào)度,可促進(jìn)兩者的協(xié)同優(yōu)化。在算法上,傳統(tǒng)多目標(biāo)粒子群算法(MOPSO)采用擁擠距離法尋找集群最優(yōu)解,局部性強(qiáng)而全局性較差。為此,首先構(gòu)造了引入模糊相似矩陣的多目標(biāo)粒子群算法(FMOPSO),以提高算法的全局性;然后綜合兩算法的優(yōu)點(diǎn),提出了混合策略下的多目標(biāo)粒子群算法(HSMOPSO)。結(jié)果表明:將一歐洲典型微電網(wǎng)作為優(yōu)化調(diào)度對(duì)象,采用HSMOPSO算法求得的非劣解集不僅更貼近真實(shí)的Pareto最優(yōu)前端,且分布廣而均勻,并且具備良好的多樣性;在微電網(wǎng)中引入儲(chǔ)能技術(shù)后,優(yōu)化結(jié)果更靠近坐標(biāo)原點(diǎn),實(shí)現(xiàn)了Pareto改善。研究結(jié)果驗(yàn)證了所提優(yōu)化算法兼具良好的局部搜索能力與全局搜索能力,同時(shí)也論證了引入儲(chǔ)能技術(shù)可顯著促進(jìn)微電網(wǎng)經(jīng)濟(jì)與環(huán)保的協(xié)同優(yōu)化。
[Abstract]:Taking the economy and environmental protection of microgrid operation as the objective to optimize the scheduling can promote the cooperative optimization of the two. In the algorithm, the traditional multi-objective particle swarm optimization algorithm (MOPSO) uses the crowded distance method to find the optimal solution of the cluster, and the locality is strong and the whole situation is poor. Therefore, the multi-objective particle swarm optimization (FMOPSO),) algorithm with fuzzy similarity matrix is first constructed to improve the global performance of the algorithm, and then the multi-objective particle swarm optimization (HSMOPSO).) algorithm based on hybrid strategy is proposed by combining the advantages of the two algorithms. The results show that, taking a typical European microgrid as the optimal dispatching object, the non-inferior solution set obtained by HSMOPSO algorithm is not only closer to the real Pareto optimal front end, but also widely distributed and uniformly distributed, and has good diversity. After the energy storage technology is introduced into the microgrid, the optimization result is closer to the coordinate origin, and the Pareto improvement is realized. The results show that the proposed optimization algorithm has both the local search ability and the global search ability. At the same time, the introduction of energy storage technology can significantly promote the cooperative optimization of microgrid economy and environmental protection.
【作者單位】： 四川大學(xué)電氣信息學(xué)院智能電網(wǎng)四川省重點(diǎn)實(shí)驗(yàn)室;
【基金】：四川省科技廳支撐項(xiàng)目(2014JY0191) 成都市科技項(xiàng)目(2015-HM01-00132-SF)~~
【分類號(hào)】：TM727

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