基于启发式的需求响应家庭能源管理系统
A Heuristics-based Home Energy Management System for Demand Response
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来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，集中在能源重新分配的问题，消费者应转移他们的能源消费模式远离高峰期和/或高电价。我们的解决方案将住宅负载分为两类：（i）固定电源设备和（ii）灵活电源设备。因此，我们制定我们的问题作为一个约束优化问题，这是非线性的，不能在数学上解决的封闭形式。然后，我们采用和比较两个著名的算法，遗传算法（GA）和和声搜索算法（HSA），以尽量减少电力费用和峰均比。这两种方法进行比较的情况下，没有发生重新分配。数值结果表明，遗传算法和混合算法分别可以有效地降低0.9%和3.98%的电力成本，降低15%和5.8%的PAR
英文摘要：
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
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