考虑家电关联与舒适性相结合的用电行为多目标优化模型

随着智能家电的广泛应用,实现用电行为优化已成为家庭智能用电的重要研究内容。从经济性和舒适性两个方面入手,提出一种智能用电环境下用电行为多目标优化模型。首先,分析了家庭用户的负载特性,并定义了可中断和可转移电器的运行约束。然后,考虑家电负载和用电习惯等各方面的约束条件,设计了家电关联最小化电费支出模型和用户用电舒适度模型,实现了多目标优化。最后,提出基于持续搜索多目标粒子群算法进行优化模型的求解。算例分析表明,多目标优化模型能有效降低用电费用并提高用电舒适性。

Multi-objective Optimization Model of Electricity Consumption Behavior Considering Combination of Household Appliance Correlation and Comfort

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important content of household intelligent electricity. Multi-objective optimization model in the environment of intelligent electricity is proposed from the two aspects of economy and comfort. Firstly, the load characteristics of the domestic consumer are analyzed and the operating constraints of the interruptible and transferable electrical appliances are defined. Then, considering the constraint conditions such as household electrical load and electricity consumption habit, the correlation minimization electricity expenditure model of household appliances and the comfort model of electricity consumption are designed to realize the multi-objective optimization. Finally, continuous search multi-objective particle swarm algorithm is proposed to solve the optimization model. The analysis of the example shows that the multi-objective optimization model can effectively reduce the cost of electricity and improve the comfort of electricity use.