## 1 Introduction  
### Motivation  
In conventional power systems, almost 20% of the generation assets exist to meet the peak electrical demand only, which occurs within 5% of the total time [1]. In order to deal with the peak demand problem in a more cost-effective way, demand response (DR) programs that enable various peak load management strategies have gained increasing interest over the last few years. These programs have recently concentrated on residential implementations in particular, since 20-40% of electric energy is consumed by residential consumers in most developed and developing countries [2, 3]. In this regard, home energy management (HEM) systems play a vital role in improving the effectiveness of DR programs. These systems enable householders to participate in DR programs easily by manually or automatically controlling the appliances regarding different parameters such as electricity prices and end-user preferences [4, 5].  
The commonly used DR methods are classified into two groups in the literature: pricing-based programs (e.g., dynamic pricing) and incentive-based programs (e.g., direct load control (DLC)). The latter group, which is based on controlling the appliances of consumers in predefined time periods, is generally considered to be a more effective tool for alleviating the peak demand [6]. However, the effectiveness of these methods is significantly influenced by the number of consumers to be involved in DR programs. Therefore, different types of incentives, such as free or very cheap electric energy at nights or weekends, or guaranteed payments are proposed to residential consumers in order to increase their willingness to be enrolled in a DR program and be involved in DR events. These incentives have contributed to the more widespread adoption of DR programs in certain countries and regions; however, on the contrary, the incentives have fallen short of targets and expectations in various regions due to several reasons such as: (i) already very low electricity prices in some areas enabled by generally high renewable energy generation in certain periods; (ii) the lack of information provided to the consumers about their consumption and the resulting costs; (iii) deficiencies and delays in informing all the end-users about the starting time of upcoming DR events before an adequate amount of time; and (iv) the concerns of the consumers about their comfort level. For the purpose of convincing more end-users to become a part of peak load management actions, various tools have been used in both the literature and real-world applications. For instance, the benefits of DR programs on the sustainability of energy and environment have been explained in more detail to end-users by mentioning their positive effects on environmental problems and future energy costs to improve their willingness. Among these efforts, the technologies which aim to inform the end-users about the DR events in a simple way--to provide all the relevant information to them in real time, and then to make a scheduling by asking about their decision and preferences--have shown quite promising results recently.  
Based on the favorable effects of interactions with the consumers on the effectiveness of DR programs, utilities and system operators have started to make use of such tools more widely. Some utilities have taken advantage of text messages to inform the consumers in an easy and fast way and to prevent spending the time when responding to the DR event invitation. Besides, some of them have preferred dedicated websites for related communications to provide relatively higher amounts of information with visual materials. These tools enable the consumers to participate in DR events easily and whenever they are convenient, and also allow utilities to observe consumer decisions in real time.