Home Energy Management Systems: Operation and Resilience of Heuristics against Cyberattacks
This addresses cybersecurity risks in residential energy management for consumers and grid operators, but it is incremental as it focuses on evaluating existing heuristics rather than proposing new solutions.
The paper tackles the vulnerability of home energy management systems (HEMSs) to cyberattacks that manipulate electricity pricing, leading to increased customer bills and grid peaks, and it analyzes the resilience of heuristic algorithms against such attacks.
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.