## 2 Demand-Side Management Classifications and Their Roles in Cost Minimization
### Classification of DSM
#### 2.1.2 Load Scheduling
The authors in [124] suggested a power line communication-based HEMS that can provide information on home energy consumption in real-time. In addition, it has the capability to make an intelligent plan for appliance control as well as optimizing power consumption at home. The HEMS consists of three modules: an advanced power control planning engine, a device control module, and a power resource management server. In [126], the authors explored a smart home energy management (SHEM) system based on the ZigBee sensor network. The authors divided the SHEM into various home networks, where each network consists of sensor nodes. Each and every home network performs different tasks by collecting the information through sensors, and on the basis of this information, it controls various home appliances. The information may be humidity, temperature, light and/or other phenomena, i.e., human movement, gas leakage, etc. Furthermore, the authors added a routing protocol named the disjoint multi-path based routing (DMPR) protocol. Using DMPR, the sensor nodes establish a wireless network with other sensors nodes and with the help of this network, it can intelligently control the system's services. Similarly, in [90], the authors explained another ZigBee network-based HEMS. This scheme is used for residential demand response application and for the reduction of overall energy consumption. The proposed HEMS consists of a HEM unit which provides monitoring and control for the consumers and a load controller that is used to collect the consumption of data from different home appliances with the help of instructions from the HEM unit. The HEM unit consists of an embedded PC that runs a GUI software application and HEM communication module. The function of the embedded PC running the GUI software application is to switch on/off the consumer appliances on the basis of a demand response algorithm while the communication module establishes a communication network between the HEM unit and load controller. On the other side, the load controller provides an interface between the appliances and the HEM unit. The proposed system is used to monitor and control consumers' actual loads according to the demand responses in order to minimize the overall energy consumption. In [127], the authors introduced HEMS, in which the energy used by the various home appliances of consumers is compared with a reference energy level at the energy portal server. The reference energy and prices at the energy portal are periodically updated according to the instructions provided by the supplier. The HEMS compares the consumers' consumption of  
Figure 6: Price predictor and ECS device. different appliances to that reference, and if the consumption exceeds the reference, the HEMS shifts the appliances into an efficient time slot where the price per kWh is low. (ii) Optimization-Based or Software-Based HEMS  
In software-based HEMS, the system consists of a framework that has the capability to schedule and manage the load at consumers' premises and also provide benefits to the consumers. These frameworks are based on different optimization algorithms, as shown in Figure 5. In [92], the authors suggested an in-home energy management system (iHEM) and optimization-based residential energy management (OREM) to reduce the energy cost and demand during peak hours. In addition, the iHEM system minimizes the consumers' bills and reduces their contribution to the peak load. The aforementioned schemes, iHEM, and OREM, are used to schedule and control the in-home appliances. The performance of the proposed OREM system has been compared with hardware-based HEMS and it was concluded that OREM outperforms hardware-based HEMS. The authors in [93; 128] proposed an efficient scheme for scheduling the consumers' energy consumption in a dynamic pricing environment. The proposed framework in [93] is based on mixed-integer linear programming (MILP) with the objective of developing a home energy controller and reducing the energy cost.