Our attention is on HVAC load since studies have shown that it accounts for 60% of all energy consumed in houses and buildings, making it a key driver of power consumption in residential and commercial structures.Each building’s power consumption has been determined in a typical way.To do this, the energy use of each piece of electric equipment was measured in four buildings, and it was discovered that the AC uses more than 60% of the energy in each one, as shown in Fig. 7.
Especially for countries like Pakistan, they provide an EC strategy focusing on the temperature variance over 24 hours. To do this, we provide eight-time slots (TSs) tailored to reducing energy use across four structures. The dynamics of building operation and the interior temperature were considered while designing the eight TSs. The AC system's energy usage is fine-tuned for each TS to minimize costs. Table 2 provides further information on each TS.
Table 2
The duration of each time slot
Time Slots | Time |
From | To |
Intelligence at night | \({(T}_{S1})\) | 0.00 | 5.10 |
A pleasant start to the day | \({(T}_{S2})\) | 4.00 | 7.00 |
Industrial mechanization | \({(T}_{S3})\) | 9.01 | 10.02 |
Dynamic lock thermal comfort | \({(T}_{S4})\) | 8.00 | 18.20 |
Compensation for peak ambient temperature | \({(T}_{S5})\) | 12.02 | 15.10 |
Closing business | \({(T}_{S6})\) | 17.04 | 18.20 |
Automation of closing business | \({(T}_{S7})\) | 18.03 | 19.04 |
Slow evening | \({(T}_{S8})\) | 19.01 | 23.02 |
-
Intelligence that is aware of nighttime conditions (TS1) is intended to optimize energy use at those times of day when it is colder outdoors. It modifies the thermostat settings to maximize energy efficiency and ensure thermal comfort.
-
When cooling operations commence with a morning soft start (TS2), they do so gradually and when the ambient temperature is normally lower. This encourages energy conservation without compromising comfort in any manner.
-
The TS3 system’s automated morning routine coordinates the activation of HVAC equipment and lights at the start of business.
-
Dynamic lock for thermal comfort (TS4) ensures maximum comfort with minimum energy consumption by locking the permissible thermostat settings.
-
The temperature at the peak is adjusted for the outside air (TS5) during the warmest portion of the day, between 12:00 and 15:00; the thermostat lock is turned off to provide optimal thermal comfort and to respond to sudden shifts in outside temperature.
-
To save energy and keep the air moving after business hours, air conditioning systems may “coast” using the close of business coasting (TS6) feature.
-
Automating the shutdown of unused air conditioning systems (TS7) at the end of work hours may reduce overall energy consumption by as much as 5 percent.
-
Energy consumption decreases as daytime temperatures lower in the evening (TS8). Changing the thermostat settings does this.
Multiple HVAC systems in four distinct office buildings were the subject of the case study. All central air conditioners are equipped with ECON, which constantly monitors energy use and the surrounding environment, relaying this data to a central hub. Based on eight TSs, a time- and sensor-based method is illustrated in Fig. 9. It is handled at the ECN layer after being performed at the IoT layer.
Data on power usage preceding and following the proposed system's installation must be collected to validate the method. The objective of this inquiry is to gather information on how electrical energy is used under typical (conventional) circumstances and to compare that information to the conclusions of the case (EMS) in which the suggested system was being used. Electrical usage is computed yearly, daily, and hourly for this purpose using data from the LESCO (Lahore Electric Supply Company) electrical bill. In this case, customers are going about their daily business without being mindful of how much energy they are using or relying on the system that is being offered.
Following the installation of the suggested system, each TS’s power use is noted, and comparisons are conducted between the two scenariosunder normal circumstances (traditional) and after the EMS is put in place. Figures 10 and 11 display the comparison findings and the EC % for each TS.
They found that energy savings were highest during the close of business automation, or TS7, when all unnecessary AC units are turned off, and lowest during peak ambient temperature compensation, or TS5 when the temperature outside suddenly rises. The thermostat lock is turned off to maintain a comfortable temperature. Even though evening slow down (TS8) and thermal comfort dynamic lock (TS4) save less energy than early business automation (TS3) and TS4, they still save more energy than (TS1) a. intelligence at night, (TS2) morning gentle start, (TS3) business automation starts, (TS4) dynamic lock thermal comfort, (TS5) compensation for peak ambient temperature, (TS6) closing business, and (TS7) automation of closing business.To give a more accurate picture of energy use, they may analyze the data from the SEMS using the data analytics offered by the IoT middleware module.The acquired information is studied in this case study to comprehend the power utilization patterns in distinct TSs and to assist in finding EC techniques that can help users minimize their energy consumption.
They are acquiring and analyzing data on the power use of four buildings. Table 3 shows a considerable decrease in the total energy units used before and after implementing the proposed system in various facilities.
Table 3
Unit savings comparison before and after the planned system’s installation
Buildings | KWH Readings | Saved units | Percent savings |
| Conventional | EMS |
Building 1 | 42,121 | 21,800 | 21,321 | 50% |
Building 2 | 22,0.85 | 16,840 | 5245 | 26% |
Building 3 | 33,480 | 25,600 | 6881 | 22% |
Building 4 | 15,360 | 12,261 | 2200 | 16% |
Considerable energy savings were achieved due to using these measures, which may save building owners money. By lowering greenhouse gas emissions, these savings may also benefit the environment. The following are some advantages of the SEMS that is being offered.
-
Real-time Monitoring: The SEMS’s multilayered design allows RT monitoring of electrical equipment. The system continually gathers and analyzes data on energy use from the HVAC units by combining sensors, actuators, and protocols for interaction. Users may optimize energy use by being thoroughly aware of their energy usage trends due to this RT monitoring capabilities.
-
Better Control: The ECON and middleware modules are integrated into the SEMS to regulate electrical appliances effectively. These parts provide intelligent scheduling and load management methods in response to incoming instructions. The network makes diverse HVAC systems perform more effectively, assuring effective resource usage and lowering the need for peak loads while balancing user comfort and energy savings.
-
Cost Savings: The SEMS contributes to considerable cost reductions in energy usage via system load management and optimization methods. It may save power costs by recognizing and effectively monitoring energy-consuming equipment, preventing waste during peak tariff hours. Intelligent equipment scheduling lets users use off-peak power pricing to save money.
-
Environmental Benefits: The SEMS supports ecological sustainability by maximizing energy use and load management. As a result, the system will lower the total energy demand, reducing greenhouse gas emissions and environmental effects. Smart energy management encourages a more environmentally conscious way of life by maximizing the sustainable and effective use of energy sources.
-
Improved Comfort: Using smart management and appliance control, the SEMS enhances user comfort. The system may aid in supplying a suitable living environment by considering the ambient temperature conditions and operating dynamics of buildings.
-
Longer Equipment Life: By employing load management measures, the SEMS contributes to extending the lifetime of the HVAC system. The technology lessens the pressure on the equipment, decreasing wear and tear by limiting excessive load demand and improving the functioning of appliances. This results from a longer lifespan, cheaper maintenance costs, and increased equipment dependability.