针对MMC柔性直流配电系统(MMC Based DC Distribution System,MMC-DCDS),从运行经济性和电压稳定性方面入手,提出了适用于MMC-DCDS的最优潮流控制策略。首先针对待研究MMC-DCDS系统的拓扑结构,明确了其可实现的运行方式和对应潮流分布特...针对MMC柔性直流配电系统(MMC Based DC Distribution System,MMC-DCDS),从运行经济性和电压稳定性方面入手,提出了适用于MMC-DCDS的最优潮流控制策略。首先针对待研究MMC-DCDS系统的拓扑结构,明确了其可实现的运行方式和对应潮流分布特点;然后结合该系统的损耗特点建立了最小网损控制策略的数学模型,并通过包含精英策略的遗传算法对该数学模型进行求解;最后结合系统各种运行方式的特性研究分析了对应的控制策略。在PSCAD/EMTDC仿真平台上搭建模型并进行时域仿真,结果表明:所提出的最优潮流控制策略可以在维持交流电压稳定的情况下,有效减小MMC-DCDS的输配电损耗。展开更多
This paper presents a new efficient algorithm for mining frequent closed itemsets. It enumerates the closed set of frequent itemsets by using a novel compound frequent itemset tree that facilitates fast growth and eff...This paper presents a new efficient algorithm for mining frequent closed itemsets. It enumerates the closed set of frequent itemsets by using a novel compound frequent itemset tree that facilitates fast growth and efficient pruning of search space. It also employs a hybrid approach that adapts search strategies, representations of projected transaction subsets, and projecting methods to the characteristics of the dataset. Efficient local pruning, global subsumption checking, and fast hashing methods are detailed in this paper. The principle that balances the overheads of search space growth and pruning is also discussed. Extensive experimental evaluations on real world and artificial datasets showed that our algorithm outperforms CHARM by a factor of five and is one to three orders of magnitude more efficient than CLOSET and MAFIA.展开更多
文摘针对MMC柔性直流配电系统(MMC Based DC Distribution System,MMC-DCDS),从运行经济性和电压稳定性方面入手,提出了适用于MMC-DCDS的最优潮流控制策略。首先针对待研究MMC-DCDS系统的拓扑结构,明确了其可实现的运行方式和对应潮流分布特点;然后结合该系统的损耗特点建立了最小网损控制策略的数学模型,并通过包含精英策略的遗传算法对该数学模型进行求解;最后结合系统各种运行方式的特性研究分析了对应的控制策略。在PSCAD/EMTDC仿真平台上搭建模型并进行时域仿真,结果表明:所提出的最优潮流控制策略可以在维持交流电压稳定的情况下,有效减小MMC-DCDS的输配电损耗。
文摘This paper presents a new efficient algorithm for mining frequent closed itemsets. It enumerates the closed set of frequent itemsets by using a novel compound frequent itemset tree that facilitates fast growth and efficient pruning of search space. It also employs a hybrid approach that adapts search strategies, representations of projected transaction subsets, and projecting methods to the characteristics of the dataset. Efficient local pruning, global subsumption checking, and fast hashing methods are detailed in this paper. The principle that balances the overheads of search space growth and pruning is also discussed. Extensive experimental evaluations on real world and artificial datasets showed that our algorithm outperforms CHARM by a factor of five and is one to three orders of magnitude more efficient than CLOSET and MAFIA.
