论文标题
基于启发式的家庭能源管理系统，用于需求响应
A Heuristics-based Home Energy Management System for Demand Response
论文作者
论文摘要
所谓的物联网（IoT）和先进的通信技术已经证明了通过需求侧管理管理住宅能源资源的巨大潜力。这项工作提出了一个家庭能源管理系统，该系统的重点是能源重新分配问题，消费者应将其能耗模式从高峰期和/或高电价转移。我们的解决方案将住宅载荷分为两类：（i）固定功率设备和（ii）灵活的电器。从那里，我们将问题提出为约束优化问题，该问题是非线性的，不能以封闭形式在数学上解决。然后，我们使用并比较了两种著名的启发式方法，即遗传算法（GA）和和谐搜索算法（HSA），以最大程度地减少电费和峰值与平均比率。将这两种方法与没有重新分配发生的情况进行了比较。我们的数值结果表明两种方法。 GAAND HSA可以有效地将电力成本降低0.9％，3.98％和标准级，分别为15％，5.8％
The so-called Internet of Things (IoT) and advanced communication technologies have already demonstrated a great potential to manage residential energy resources via demand-side management. This work presents a home energy management system in that focused on the energy reallocation problem where consumers shall shift their energy consumption patterns away from peak periods and/or high electricity prices. Our solution differentiates residential loads into two categories: (i) fixed power appliances and (ii) flexible ones. Therefrom, we formulate our problem as a constraint optimization problem, which is non-linear and cannot be mathematically solved in closed-form. We then employ and compare two well-known heuristics, the genetic algorithm (GA) and the harmony search algorithm (HSA), to minimize electricity expense and peak to average ratio. These two approaches are compared to the case where no reallocation happens. Our numerical results show that both methods; GAand HSA can effectively reduce the electricity cost by 0.9%, 3.98%, and PAR by 15%, 5.8%, respectively
