## 2 Demand-Side Management Classifications and Their Roles in Cost Minimization
### Classification of DSM
#### 2.1.2 Load Scheduling
The home energy controller controls different household energy appliances. With the help of this framework, PAPR can be reduced. The authors in [94], investigated an intelligent HEM algorithm to manage the energy consumption of high power rating household appliances. In addition, it ensures that the base/critical load is supplied at all times. In this HEM algorithm, the total consumption of each consumer is kept below a certain threshold (kW) where the threshold is updated regularly after one hour. Moreover, the authors presented a load scheduler to optimize the energy consumption of the consumers for dynamic price per kWh. According to this scheduler, the consumers schedule their household appliances in an efficient way in order to get a reward from the suppliers and to reduce their electricity bills. In [113], the authors used MILP and a heuristic approach to design a household energy management system. This household energy management system uses an eBox architecture that consists of a control logic unit (CLU) and an optimization module (OM). The CLU controls the overall system while the OM is responsible for selecting an optimal schedule on the basis of MILP and heuristic approach. The CLU collects signals from the consumer shiftable appliances or from the sensors deployed in the vicinity of these appliances and then dictates the OM to commence the optimization process and select an efficient schedule to reduce the energy consumption. The OM then communicates this efficient schedule to the CLU where the CLU implements it on the high power rating appliances. The high power rating appliances considered in this paper include water heaters, clothes dryers, cooling units, etc. **Conclusions of the subsection:** In this subsection, we discussed the various types of DSM which consist of direct load reduction and load scheduling. Direct load reduction was further classified into two groups, i.e., energy efficient appliances and energy efficient building. Similarly, the load scheduling was divided into two categories, i.e., centralized and decentralized DSM schemes. Moreover, we categorized the load scheduling into three subparts which included DSM based on energy pricing, DSM based on energy consumption scheduling (ECS), and DSM based on home energy management (HEM). In addition, we also categorized DSM into two categories on the basis of the optimization type used in DSM modeling and the solution methodologies used in the model solution. We also summarized the available performance metrics and provided a detailed review of the literature from an optimization perspective as well as from an energy pricing perspective and tabulated it in Tables 6-8 respectively. We identified some of the areas which need research attention. These areas include EeA, EeB, and the collective attainment of performance metrics. In the literature, very little work has been done on EeA and EeB; therefore, these types of DSM need further elaboration. Similarly, from Table 6, we can say that, in the literature, a unified framework with all the performance metrics mentioned in Table 6 collectively achieved is missing. Therefore, a unified framework needs to be modelled where all the performance metrics regarding DSM are achieved.