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Family Energy Management Based on Non-dominant Sequencing Genetic Algorithm

机译:基于非显着测序遗传算法的家庭能源管理

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摘要

The demand response of home users is very important for the realization of smart grid. This article first classifies household appliances, through the family electricity cost minimum and power grid stability of maximum, puts forward a multi-objective optimization problem (MOP), and use the pareto optimality, by introducing the elite strategy of non dominated sorting genetic algorithm (NSGA-II) to solve it. Simulation results show that this method can effectively balance the demands of residential users and power grid.
机译:家庭用户的需求响应对于实现智能电网非常重要。 本文首先通过家庭电力成本最低和电网稳定性,提出了多目标优化问题(MOP),并通过引入非主导分类遗传算法的精英策略( NSGA-II)解决它。 仿真结果表明,该方法可以有效地平衡住宅用户和电网的需求。

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