## 4 Current and Advanced Methods in BEMS
### Demand Response (DR)  
DR is a set of actions that reduce or shift electricity to improve electric grid dependability, manage electricity costs, and provide systems that incentivize load shifting or shedding when the grid is near capacity or electricity prices are high. The development of DR has been highlighted as a critical national goal for improving electricity markets and system dependability [113]. The purpose of DR solutions is to reach the electric shed savings targets while minimizing any negative consequences for building occupants or processes [114]. Direct load control (DLC) and indirect load control (ILC) are the two main categories of DR approaches (ILC). DLC is a program in which utility companies reward customers for having direct control over their chosen loads. The ILC technique, on the other hand, allows AMI to participate in the optimization process. With distributed decision makers, the utility grid shares either the day-ahead load profile projection, the dynamic energy retail price, or both. All consumers have access to this information, and by using it, they might strive to enhance their benefit (i.e., lower their consumption cost) cooperatively or competitively [115; 116]. Home appliances can be classified into three categories based on their potential to participate in DR: baseline loads (lighting, cooking stove, etc. ), burst loads (clothes dryer, dishwasher, etc. ), and regular loads (HVAC system, refrigerator, etc. ), with implemented numeric and logistic algorithms that are solved based on the finite state machine (FSM) and spring algorithm [117]. To obtain the desired goal, a unique technique of arrangement of those household loads is divided into NINSLs (non-interruptible and non-schedulable loads), INSLs (interruptible non-schedulable loads), and SLs (schedulable loads), and solved with a genetic algorithm [118]. The proposed model has shown three categories of loads: fixed, flexible, and uninterruptible, which are optimally scheduled under the time of use (TOU) tariffs based on mixed-integer linear programming (MILP) to minimize consumption and cost [119]. Moreover, DR is currently a viable approach for dealing with the problem of growing peak demand on the grid. In order to reduce peak energy consumption or demand, the scheduling of residential or industrial energy use in each appliance is optimized [120]. In [121], an interactive control unit approach was demonstrated that uses peak clipping techniques to reduce peak demand with a day-ahead scheduling mechanism that uses load shifting strategies to optimize the load. A new heuristic demand response technique has been developed for appliance consumption scheduling in order to decline the peak-to-average ratio (PAR) of power demand [116]. Peak demand can also be reduced through load shifting from on-peak to off-peak or enhancing TOU tariffs [122; 123; 124]. If the consumer is not interested in rescheduling the loads for off-peak hours, they may increase the temperature of the HVAC system. As a result, consumers could feel somewhat uncomfortable for a while, but be able to decrease the temperature setting during off-peak hours [125]. In the same way, lighting intensity can be reduced and increased during on-peak and off-peak hours, respectively. A smart plug can be utilized to prevent phantom power. If the priority of comfort is determined by consumer needs over time, the time gap must be filled with either renewable energy (RE) or energy storage systems (ESS). The presence of PV and EES can help to maintain the indoor temperature by using inverter-based AC, with ESS compensating for peak-hour demand and when there is less RE generation [119]. Coordinating the operation of electric vehicles (EVs), PV units, and BESS with an improved decision-tree-based algorithm can be used reduce peak demand in residential distribution networks [126]. The peak reduction in power and prediction of long-term load forecasting for over 300 homes were studied, focusing on peak shaving and load shifting with intelligent devices [15].