Internet of Things (IoT) and advanced communication technologies have demonstrated great potential to manage residential energy resources by enabling demand-side management (DSM). Home energy management systems (HEMSs) can automatically control electricity production and usage inside homes using DSM techniques. These HEMSs will wirelessly collect information from hardware installed in the power system and in homes with the objective to intelligently and efficiently optimize electricity usage and minimize costs. However, HEMSs can be vulnerable to cyberattacks that target the electricity pricing model. The cyberattacker manipulates the pricing information collected by a customer's HEMS to misguide its algorithms toward non-optimal solutions. The customer's electricity bill increases, and additional peaks are created without being detected by the system operator. This article introduces demand-response (DR)-based DSM in HEMSs and discusses DR optimization using heuristic algorithms. Moreover, it discusses the possibilities and impacts of cyberattacks, their effectiveness, and the degree of resilience of heuristic algorithms against cyberattacks. This article also opens research questions and shows prospective directions.
翻译:家庭能源管理系统(HEMS)能够自动控制家庭内使用DSM技术的电力生产和使用。这些HEMS将无线地从电力系统和家中安装的硬件中收集信息,目的是智能和高效地优化电力使用和尽量减少成本。然而,HEMs可能易受针对电价模式的网络攻击。网络攻击者操纵客户的HEMS收集的价格信息,错误地引导其算法走向非最佳解决方案。客户的电费上涨和创造更多的峰值而不由系统操作者检测。这一文章在HEMS中引入基于需求的DSM(DR) DSM,并讨论使用超理论算法进行DR优化的问题。此外,它讨论了网络攻击的可能性和影响、其有效性以及超自然算法对网络攻击的适应程度。这篇文章还开启了研究问题并展示了未来方向。