Saad Dilshad

Received: 9 October 2019 Revised: 4 August 2020 Accepted: 18 September 2020 DOI: 10.1002/eng2.12312 RESEARCH ARTICLE Design of home load management system for load rationing in Pakistan Muhammad Bilal Butt1 Saad Dilshad2 Muhammad Shoaib Saleem3 Naeem Abas1 Shoaib Rauf1 1 Department of Electrical Engineering, University of Gujrat, Hafiz Hayat Campus, Gujrat, Pakistan 2 Department of Electrical and Computer Engineering, COMSATS University, Islamabad, Pakistan 3 Department of Electrical Engineering, University of Management and Technology Lahore, Sialkot Campus, Pakistan Correspondence Naeem Abas, Department of Electrical Engineering, University of Gujrat, Hafiz Hayat Campus, Gujrat, Pakistan. Email:- Abstract The fast-growing electricity demand in Pakistan and other developing countries has posed a severe challenge to electricity distribution systems. Indeed, most of the utility companies have to follow a trend of load shedding to face this difficulty. Load shedding is the “art” of managing the load demand by shedding loads in critical situations where the demand is higher than the total generation to avoid system failure. Although electricity utilities are suggesting consumers reduce the load during peak hours in their monthly bills, the consumers are not willing or aware of this. It is clear how tedious and tiresome it is to remind the customers what the peak hours are, and manually switch off/on the heavy load during peak and off-peak hours. The estimated cost of the system is around 43$ and 28$ with and without Global System for Mobile Communications module for message notification. Moreover, the distribution feeder has a specific capacity to bear the load in peak hours after this is automatically shut down the whole feeder. In this paper, the simulation analysis of a single-family house is performed for automatic load reduction during peak hours in Proteus software. A hardware prototype is then designed and applied so as to validate the proposed control system. The results show that the proposed scheme allows for an efficient peak shaving during peak hours. For some typical domestic and commercial consumers, the financial benefits are also calculated. It is concluded that the payback period of this device is almost 1 month if it reduces 50% of load during the 4-hour peak time. The proposed system may be implemented as a single additional tool/span is already available energy meters and may quickly be adopted by electric utilities of developing countries to avoid the load shedding trend. KEYWORDS demand side management, load shedding, peak hours, smart metering This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Engineering Reports published by John Wiley & Sons Ltd. Engineering Reports. 2020;e12312. https://doi.org/10.1002/eng2.12312 wileyonlinelibrary.com/journal/eng2 1 of 17 BUTT et al. 2 of 17 1 I N T RO DU CT ION Electrical Energy is invisible, a universal commodity that is immediately available in most of the world, and it has been recognized as an everyday consumer need.1 Renewable Energy (RE) is used to aid the primary energy demand in the form of solar PV,2 solar thermal,3 wind energy.4 The intermittent nature of RE,5 harmonics,6,7 and reactive power problems8 halts the performance of the power system by originating stability concerns in the power system.9 The use of Flexible AC transmission controllers and energy storage devices (batteries, fuel cells, pumped, hydrogen and compressed air storage) are widely used around the world.10-12 Due to the increasing population and low economic growth, Pakistan is suffering from an electricity crisis from the past decade.13 On the other hand, the world is moving toward innovations in electronic appliances. Everyone wants comfort and ease in one’s life, and modern appliances are increasing rapidly. A load of an ordinary person’s home is doubled, at least due to modern appliances. The current electricity generation is unable to meet electricity demand. The gap between demand and supply was reported around 6000 MW, 5201 MW, and 7000 MW in 2012, 2015, and 2017, respectively,14-16 which have resulted in a load shedding hours reaching to 10-12 and 16-18 hours reaching in urban and ruler areas of Pakistan. The new induction of electricity resources was 7775 MW and 3673 MW in 2017 and 2018, and total capacity after these additions reached 37 634 MW by the end of FY2018.17 There are two possible solutions to this problem; one is to increase the generation, and second is the load management in peak and off-peak hours. The electric utilities in Pakistan have different peak and off-peak timing in summer and winter with total peak hours duration of 4 hours. Pakistan’s Water and Power Development Authority (WAPDA) is generating electricity from different sources, for example, furnace oil, hydel, gas/Liquefied Natural Gas (LNG), coal, nuclear energy, and renewable energy and their share are demonstrated in Figure 1.17 It clearly shows that the contribution of furnace oil is more significant, which is not suitable for the environment due to the high emission of CO2 .18 The considerable emissions in the world are mainly due to the burning of fossil fuels like coal, oil, and gases. First time in the Paris agreement, world representative decided to take some stern steps for the betterment of the climate, it was decided to control the maximum difference in the temperate of the earth below than 1.5 or 2◦ C until 2030.19,20 Electric power distribution companies encourage their users to use the heavy load including, air conditioner, heater, electric motors, iron, and so on, in off-peak hours instead of peak hours. However, its impact can be reduced by controlling and optimizing the available resources.21-23 The load management system is essential in the scope of energy management as it relates to the economy and system efficiency.24-27 A considerable amount of research work is done on several demand-side load management (DSLM) techniques, such as load control,28 Global System for Mobile Communication (GSM)-based remote controlling system,29 smart load management,30 evolutionary priority algorithm,31 DC/AC hybrid Grid32 and demand-side management using PV system,2,33 and so on. Some other demand-side load management techniques are peak clipping, valley filling, and load shifting, which are the direct control methods of high-power consuming loads. The limitations of DSLM methods are that they can only be implemented for those loads which are versatile. Similarly, there are many systems based on different technologies, which provide automation for homes or offices. With time, FIGURE 1 Share of electricity production by different fuels in Pakistan BUTT et al. 3 of 17 these systems demand some advancement in them. A more reliable and dependable system, with some amendments in infrastructure, replaces its precursor. Sakthivel et al proposed to design a system to minimize the energy consumption for the specified customer in planned duration instead of load shedding. There will be a GSM-based remote controlling station from where we could send control information that will consist of maximum power consumption and restricted time-period. If the user uses more power than the permitted power, after a warning, his power supply will be disconnected automatically by the system.29 An evolutionary priority algorithm-based demand side management system is proposed in Reference 31, the system is based on time, and device-based priority for consumers that they can set the devices and as well as the timing of their use in the demand meter and the EPA enable control helps them to achieve the minimum load based on their use. Labib et al30 have presented a design of smart load management system (SLM) scheme which can be used efficiently to satisfy consumers during emergency demand (light and fan) when available power is not sufficient concerning its demand. Rani et al34 have proposed the smart grid implementation in Pakistan to resolve stress situations in the electrical energy system by responding to demand. The primary aspect of their work was to manufacture an economical GMS-based smart energy meter that can send information of instant power usage on the customer’s side to the grid via GSM modem. Each user was permitted to use a specified load if the load exceeds the load limit, short message service (SMS) caster sent a notice to reduce the load within the specified limit to avoid power cut-off after 10 minutes. The limitations of their work are that the proposed system cut off the complete power of the individual user. A generic demand side management (GDSM) scheme is presented by in Reference 35. The GDSM is proposed to decrease peak-to-average ratio, electricity cost, and waiting time of appliances. Review on information processing for a renewable energy system using two-way communication for demand side management (DSM) and demand response system. The use of DSM is gaining popularity due to the maturity in IT industry and meanwhile rising cost and demand for electricity. They have presented a review of different control strategies for DSM. A review of Internet of things (IOT) and cloud computing for accessible data collection, and communication for every engineering field is presented in Reference 36. Some of them are needed continuously human interference, very costly, complex and challenging to implement on a large scale. Home load management is a very vast field, and many researchers are working on it to manage the demand and supply. The proposed, the designed control system is most suitable in term of performance and simple technique of control using an Arduino controller. Because the conversion of all the grids to a smart grid is not happening in a short time, this requires a large infrastructure, capital, and proper training of the utility workers. However, this system has an advantage like its hardware is less complicated and cost-efficient than other techniques and it can work standalone system without any monitoring. The paper is organized as follows: Section 2 covers the proposed methodology and proposed a model of home load management and control system, estimation, and design of its parameters. Section 3 includes results and discussion. The conclusion and future outlook of this research are described in Section 4. 2 PROPOSED HOME LOA D MANAG EMENT DESIGN Electric power distribution company can install this system at the consumer end. It consists of a current sensor which can be used as a current sensing device that will detect the load current continuously. When the peak hours come and if the load current exceeds the calculated set range from the threshold level, then the microcontroller will send the trip signal to the attached relay to switch off the connected heavy loads. When the off-peak hours come, it will give the alarm/buzzer if a consumer wants to use any heavy load during this time. This system will help us to manage between the demand and supply to avoid load shedding during peak hours. It also gives the consumer to low-cost tariffs and encourages the use of heavy load in off-peak hours without shutting the load during high-cost tariff time and when this time of use meter control is connected. The key benefits of this system are summarized in Figure 2. In this research, the main focus is maintaining the load current of a particular feeder of an electric utility in a permissible limit to avoid the load shedding during the summer season. This research project’s main objective is to manage the home’s heavy load appliances’ automatic control during peak and off-peak hours. The electric utility will control the bulky load devices, including AC, electric heater, electric iron, and motor, with calculated base load values as feed in the microcontroller. AC current value is measured by the current transformer/current sensor from the consumer’s home’s service mains. This AC current value is an analog signal that must be converted into a digital signal so that microcontroller can read this value and send the signal to the operational relay to switch on/off the load during peak and off-peak BUTT et al. 4 of 17 FIGURE 2 Key benefits of the proposed load management system hours.37 This will lead us to give the load control in peak hours and encourage the consumer to use the heavy loads in off-peak hours. This technique is different and easy to apply from the literature review techniques because no human intervention is required in this system. In a broader sense, if electric utility uses this technique to the whole town/city, then electric utility can overcome the problem of load shedding in that area because no peak hours will come. The design system to manage the home load consists of the microcontroller (Arduino UNO) and current sensors, for example, Current Transformer (CT) and ACS712. This system will help to switch off the home appliances during peak hours automatically. This microcontroller system will help to switch on the loads during the off-peak hours and encourage the consumer to consume the electricity at a low-cost tariff. The design of this will be simple, cost-effective, and easy to understand by the consumer. In Pakistan, people face unusual electricity shut down due to the high peak demand during the summer season. Furthermore, they are facing the issue of increasing the cost of electricity, global warming, and climate change. Research on RE applications like solar thermal,38 net-zero energy buildings,39 and climate-friendly substances and applications like natural refrigerant,40 and fuel cell-based micro-combine power systems41 are getting considerable attention in Pakistan. There is a need for electricity utility to analyze each home appliances’ electricity usage and manage its use in peak demand hours. Some devices are consuming unusually high power consumption, and it should be turned off at peak hours. 2.1 Home load calculation and management First of all, the Home load is calculated for each home appliances so that electric utility can set a threshold value for tripping the load and the Diversity Factor and Demand Factor. Their diversity factor is defined as the ratio of the individual maximum demand of the system to the maximum demand of the whole system. Diversity Factor (DF) = Sum of Individual Maximum Demand Maximum Demand of the System (1) BUTT et al. 5 of 17 The diversity factor and the load are very closely related to each other.42 The demand factor is the ratio of the sum of maximum demand of the system to the system’s whole connected load. Demand Factor = Sum of Maximum Demand Total Connected Load (2) Consider the example that a home has the total connected load of 100 A but has the maximum demand on a peak time is 60 A; hence the demand factor is 0.6 that is less than 1. Now, separate loads of the low power appliances and loads of heavy/inductive appliances will be calculated by using the real-time example of a typical home in which all the appliances for example, fans, electric motors, AC, washing machine, Television (TV), energy savers, microwave oven, electric iron, refrigerators, electric heaters, and so on. A typical home load classification is given in Table 1, and the AC current rating of some appliances along with their power ratings is mentioned in Table 2. From the above calculations, the home’s total connected load is 38 A, in which 33.25 A are of heavy loads. The use of these appliances can vary season to season. The base load of the above-mentioned home load is 9.9 A. 2.2 Design of control system The block diagram of the load management and control system is shown in Figure 3. The main components of the proposed method are a current transformer, Analog to digital converter, Arduino UNO microcontroller, power supply, LCD, T A B L E 1 Home load types and classification32 Load type Power (Pmax ) (W) AC/DC Appliance Urgency Usage time duration Primary 150 Both AC/DC Fans AC/DC energy savor, LEDs Mobile/Laptop and small gadgets chargers, TV, Computer, AC lights, DSL adapter First Full Day Regular (necessary) - Both AC/DC Fridge AC/DC Deep Freezer Uninterruptable Power Supply (UPS) Second Full day Regular (luxury) 1200 DC DC inverter AC Third On Demand Brust (luxury) - AC Pump motor, washing machine, juicer electric oven, Irons and electric gas heaters Fourth Occasionally T A B L E 2 Home load calculation43 Appliances Quantity Power (W) Current (A) Total current (A) Energy saver 30 24 0.10 3.27 Fans 5 100 .454 2.27 Electric iron 1 1000 4.54 4.54 TV 1 100 0.454 0.454 AC 1 2400 10 10 Refrigerator 1 200 0.909 0.909 Heater 1 2000 9.09 9.09 Microwave oven 1 1500 6.81 6.81 Washing machine 1 500 2.27 2.27 Electric motor 1 1.5 5.08 5.08 Total load 38 BUTT et al. 6 of 17 FIGURE 3 Proposed control system block diagram relay drivers, and relay according to the load current. ACS712 IC can also be used as a current sensor instead of the current transformer if the current value is less than or equal to 20 A. The controller is connected with the current sensor as a feedback loop. A real-time clock and time adjustable is also attached as the input of the controller. LCD will display the real-time and value of the load as the output of the controller. The current sensor’s output is associated with the heavy loads and depends upon the amount of the load current. A buzzer will indicate that off-peak hours are going on. 3 R E S U LTS AN D D ISCU SSIONS The Arduino sketch was made for the load management system design on Arduino compiler IDE, and a flow chart of the proposed control scheme is illustrated in Figure 4. The complete design, including Arduino UNO, current sensor, and connected devices, are made and simulated on Proteus Professional Software. The circuit diagram used for simulation in Proteus is shown in Figure 5. The current sensor ACS712 is used instead of CT to measure the current of active loads. A current sensor is continuously monitoring the load current of the home appliances to check the value of the load current. If the amount of the load current is higher than the set value, then Arduino will send the trip signal to the relay to switch off the heavy loads until the desired amount of the load is reached. A real-time clock is also attached to measure the peak and off-peak time. There are four electric lamps, and one motor is used as a heavy load in this simulation. Each electric lamp consumed 2.85 A, and the motor consumed 9.9 A. These loads are connected with Arduino UNO via a relay. 3.1 Operation during peak hours In this simulation, the set time for the peak hours is 6:00 pm to 10:00 pm, and the rest of the time is off-peak hours. The current threshold value should be less than 10 A. Arduino will only operate when both these conditions come true. The total load consumed by the four electric lamps (11.4 A) and one motor (9.9 A) is 21.3 A, as shown in Figure 6A. During peak hours, the current sensor ACS712 measures the value of the current that is 21.3 A. It means that all the attached loads in working condition then the Arduino controller immediately send the trip the signal to the first relay and shut down the first lamp. The value load decreased from 21.3 A to 18.45 A. But this value is still higher than 10 A, so after the delay of 2 seconds, Arduino again sends the trip signal to relay two and shut down the lamp 2. The value of load current BUTT et al. FIGURE 4 7 of 17 Flow chart of Arduino Sketch now decreased to 16 A, as shown in Figure 6B. Initially, the current value was 21.3 A, and when the peak hour came to the control system operates, it turned off the first two appliances, and the load current reached up-to 16 A, which is still higher than the set load current of 10 A for peak hour times. Then the control system again operates, and another appliance is off, and now the load current drawn by the appliances is less than the set limit. The current value is fluctuating between 21.3 A and 15.6 A. When the peak hours (6 pm to 10 pm) come, all the heavy loads have shut down, and load value decreased to the desired base value of 9.9 A. This system is very flexible in terms of peak hours because the peak hours of the electric utility varies from area to area and season to season. The Customer Support Representative (CSR) of an electrical power BUTT et al. 8 of 17 FIGURE 5 Circuit diagram of the simulation during off-peak hours FIGURE 6 Variance of current during peak and off-peak hours (display of connected LCD) company can easily change the value of peak hours by change the Arduino code in the system installed at the consumer end. After this, all the lamps will shut down, and the value of the load current reaches the desired value of 9.9 A. Now only one load is working and consuming the 9.9 A, as shown in Figure 6C. 3.2 Operation during off-peak hours During off-peak hours, Arduino sends the signal to the attached buzzer that will remind the consumer that peak hours are gone, and now they can operate their devices as per their choice. It also encourages the consumer to use their heavy appliances during these hours so that electric utility can maintain the balance between demand and supply during the summer season. The control scheme also does not turn off any device during off-peak hours. Hence, all the appliances run smoothly during that time, with this control system connected to their main electricity utility meter. 3.3 Hardware implementation A prototype of the load management system is made and evaluated using a project-based scenario with three current sensors to measure connected load currents of all different kinds of loads like lighting, necessary and general loads. For implementation, testing, and evaluation, the smaller current values are used to perform a safe, practical demonstration. BUTT et al. 9 of 17 Three lamps of 100 W each are connected to depict the different load scenarios for the experiment. During off-peak times, these three lamps can be turned ON and OFF any time. But during peak hours, only a specified amount of the load can be used. In this case, a total limit of 0.55 A was set to check the proposed design’s implementation. These are the outputs that we got on the LCD screen during different situations. Initially, the input is applied to the energy meter, but there was no load connected with it at that time. Figure 7A shows the different loads’ readings when there is no load on the system. Then all three lamps depicting lighting, necessary, and luxury loads. Readings of the various loads when 100 W of the lamp are connected representing each load are seen in Figure 7B. After 1 minute and 30 seconds, the energy meter sends a notification by SMS to the user stating to reduce the load within limits because peak time will start soon. After 30 seconds of this notification, the energy meter sends the other notification stating that peak time has been started, so keep your load within the limit to avoid power cut off. When peak time starts, the energy meter checks the consumer total load current and compares it with the allowed load. In our case, it is 0.55 A. The energy meter automatically disconnects the luxury load, which can be seen in Figure 7C. Because the total current is more than the limit and sends the notification to the user about this, the energy meter again checks the total current. If the load current is still higher than the sanctioned load, it disconnects the necessary load, as shown in Figure 7D, and sends a notification about this. When the peak time finishes, the energy meter automatically connects all the disconnected load, as shown in Figure 7B, and sends the notification. When the voltages are below 180 V, the energy meter cut off the power to save the appliances from damage, as shown in Figure 7E. The GSM also sends notification of these situations to the consumer’s mobile by GSM. All the notifications can be seen in Figure 8. The GSM module is used to send a customer notification on the consumer mobile phone for informing about the current state of the decision taken by the meter. Figure 8 shows some messages/notifications received on mobile whenever some action is taken by the energy meter during different situations. 1. About 30 seconds before the peak time. 2. When peak time starts. F I G U R E 7 (A). All load is off, (B) all load on during off-peak time, (C) during peak hour Luxury load turned off, (D) necessary load turned off to meet the load requirement during peak time, (E) protection of electrical appliance against low voltage BUTT et al. 10 of 17 FIGURE 8 Notifications received on mobile through GSM module connected with meter 3. 4. 5. 6. 3.4 If the load is higher than the allowed load during peak time. If the load is still greater than the permitted load during peak time. When off-peak time starts. If voltages are under 180 V. Cost of load management device The electric utilities in Pakistan decide to change the electric meter by themselves. However, the energy meter’s expense is charged from the costumers on installments in their electricity bill. It is not an issue for the utilities to decide if this benefits them in the long run and the Government in Pakistan also has a policy to give subsidy for domestic and agriculture consumers. The estimated cost of equipment for load management devices is presented in Table 3. This cost is almost identical to the cost of an energy meter installed at domestic consumer premises. The circuit diagram of the proposed system is illustrated in Figure 9. 3.5 Impact on consumers electricity bills There are different types of meters applied for domestic, commercial, industrial, and agriculture users. The tariffs for TOU meters are almost similar for various applications with a slight difference. Electricity tariffs by electric utilities in Pakistan for different applications are presented in Table 4. T A B L E 3 Equipment cost for load management device Serial no. Item name Quantity Per unit cost (PKR) Total (PKR) 1 Arduino Mega 1 1100 1100 2 ACS712 Current sensors 3 250 750 3 Transformer 1 300 300 4 Other Electronic Components 1 200 200 5 LCD 20 × 4 1 570 570 6 Switch board 1 200 200 7 Power supply 2 250 500 8 Arduino cables 2 150 300 9 Relay 5 150 750 10 GSM module 1 2500 2500 Total including GSM 7170 PKR ≈ 43$ Total (without GSM) 4670 PKR = 28$ BUTT et al. 11 of 17 FIGURE 9 Implementation of the proposed load management system T A B L E 4 Electricity tariffs in used by electric utilities in Pakistan 44 Meter type Consumer and meter type Peak per kWh (PKR) Off-peak per kWh (PKR) A Residential (A1-03) 20.70 14.38 Commercial (A2) 21.60 15.63 B B1 (b) B2 (2) B3 Industrial 1. Up-to 25 kW 2. 25-500 kW at 400 V 3. up to 5000 kW (at 11,33 kV) - - D1-(b) Agriculture >5 kW 18.60 11.35 A cost analysis to check the financial saving with the proposed home load management system is applied to domestic and commercial applications. The peak and off-peak unit’s prices are- and- PKR per kWh (1 kWh = 1 Unit). Table 5 shows a calculation for estimated consumed units 800 off-peak and 400 peak hours, and the estimated bill is calculated. The peak and off-peak hours are 20 and 4 hours throughout the year and with different timings during summer and winter. The peak hours for December-February, March-May, June-August, and September-November are 5 pm-9 pm, 6 pm-11 pm, 7 pm-11 pm, and 6 pm to 10 pm, respectively. The typical bill without any load management system is around 26 609 PKR. A similar statement is also obtained from one of the utility websites. The utility’s electricity bill calculation results show a 26 604 PKR bill, and almost there is 34.5% of government taxes involved in the billing in Pakistan. They are then assuming only a 50% load reduction during the peak hours. The resulted electricity bill is calculating as- in Table 5 and similar in Figure 10B. This shows an around 5500 PKR ≈ 33 USD saving, the saving of 1 month is enough to pay back the cost incurred on these devices. T A B L E 5 Estimate of energy Saving with proposed load management system44 Cost of electricity Estimated unit Tariff per kWh consumed Meter type Residential (A1) (PKR) Cost of Total cost of electricity when peak load Total electricity Saving in (without load management) reduced to 50% bill (with load money (PKR) Peak load management) (50% Peak load (1 Unit = 1 kWh) electricity (PKR) [PKR] Peak Off-peak Off-peak Peak Off-peak Peak Without tax With tax (34.5%) reduced to 50% [PKR] reduction) - 11 504 19 784 4140 - 5568.3 6480 34 171.2 11 664 800 400 8280 26 609.5 With tax (80%) Commercial (A2c- 800 600 12 504 - 45 835.2 12 of 17 F I G U R E 10 BUTT et al. Calculated bills for the estimated cost (A) domestic (without load management) (B) domestic (with load management) (C) commercial (without load management) (D) commercial (without load management). Source: Reference 45 BUTT et al. 13 of 17 Similarly, another commercial application scenario is checked and due to very high government taxes on the consumed electricity is around 80%, and almost double saving is achieved with this system. Around 11 664 PKR ≈ 70 USD saving can be archived by reducing only half of the peak load utilizing this load management system. The estimated bill calculated from the utility website shows that with and without a load management system gives around 45 544 PKR and 34 255 PKR bill for 1 month. This significant difference is also due to the very high government taxes on the used electricity amount. This device’s short time benefit is to tackle the high energy demand efficiently without applying a forced load shedding on a whole feeder. The long term benefits of such devices are the amount of money it saves for the consumers as 4 hours of peak load, mostly in the evening time, and almost 60% increased tariff is applied during peak load time. After this increased tariff, there is a lump sum of 23% of government taxes applied to the amount of total electricity bill. Thus a slight increase in electricity kWh during peak hours may increase the electricity bill a lot. Therefore, such devices are very beneficial for the consumer to manage their electricity bill. 3.6 Research implementation on GEPCO subdivision for load shaving The detailed research objectives to maintain the balance between demand and supply during peak and off-peak hours to overcome the problem of load shedding is explained by proposing this system for a Gujranwala Electric Power Company (GEPCO) feeder. The results of this simulation can be implemented on any GEPCO subdivision to get the desired output. Consider an 11 kV feeder of Wazirabad GEPCO sub division Wazirabad was chosen for the desired data collection. The data were collected from the Wazirabad GEPCO subdivision for a single feeder. It has the 9939 consumers on this feeder, and it can bear the maximum load of 400 A at 11 kV. All these consumers consume the 6.86 MW power of connected load of 12 MW of all the attached distribution transformers; If the current reaches the value of 400 A, the distribution feeder will get overload and trip. All the consumer will face the load shedding after tripping the feeder. On a typical day, the consumer may not use the maximum load of more than 10 A; however, many customers will use it. Different consumers may use different load in peak hours. The electric utility can have assumed their load consumption from consuming kWh, as mention in the bill. It is extracted the data from the monthly billing report of the Wazirabad Subdivision that most of the consumers are consuming the load value less than 10 A but still 3439 customers that are consumed the load greater than 10 A in peak hours, as shown in Table 6. However, not all consumers at a time are using the same load value in peak hours. The home loads are running on a different current value higher than 10 during off-peak hours. When the peak hours (4 hours of peak time) come, all the heavy loads have shut down, and load value decreased to the desired base value of 9.9 A. This is how electric utility can run the home or commercial load during peak hours down to a base level to avoid unnecessary load shedding in the summer season. This system is very flexible in managing peak hours because the electric utility’s peak hours vary from area to area and season to season. The Customer Support Representative (CSR) of an electrical power company can easily change the value of peak hours by change the Arduino code as per the requirements. These 3439 customers are increasing the load current on the feeder of 11 kV due to which feeder get overload and trip in peak hours, and unscheduled shedding will occur. There is a need to reduce the load of the consumer by applying the research results, and electric utility will get the reduction of load in peak hours. The designed control system will reduce the load in peak hours as set in the simulation. The value of load current can vary according to different environments and areas. The 3-day graph is made to explain the reduction on load during the peak hours after applying the home load management scheme. The segments of consumers are shown on the X-axis, and the value of load current (with and without control) is plotted in YZ-axis (see Figure 11). T A B L E 6 Load management in peak hours (4 h in evening) No. of consumers Load current range (A) Total load current without control system (A) Total load current with control system (A) 1-1500 1–2 3000 3000 - 3–5 5000 5000 - 7-10 8000 8000 - 10-25 25 000 14 000 41 000 30 000 9939 BUTT et al. 14 of 17 F I G U R E 11 Consumer segments load currents (with and without applying control system) 4 CO N C LUSION S Electric utilities want to reduce the load during the peak hours and encourage the user to use the appliance in off-peak hours to manage the load between supply and demand to avoid unscheduled load shedding. A home load management system for distribution utilities to prevent unnecessary load shedding during peak hours is proposed in this research. The Arduino-based smart load management system is simulated and tested using Proteus software. It can be a very cost-effective load management system. This system’s hardware is less complicated and can be applied easily on the heavy load consumer houses. The system design can switch off the heavy load during peak hours without any human interference and encourage the consumers to use these heavy loads during off-peak hours. The cost-effectiveness, easy implementation, SMS notification, and only a 1 month payback period are key features of the proposed home load management system. Such projects are necessary for both the consumers as well as a utility as both can benefit from this. Therefore, it is highly recommended to both consumer and electric utilities to control the use of heavy home load during peak and off-peak hours as well a considerable amount of saving for both domestic and commercial consumers is achieved by employing this. This will lead the electric utilities to avoid load shedding in peak hours due to an imbalance between demand and supply, and the consumer can avail the benefit in the form of less billing. Further research needs to be conducted to improve the control system’s designs by adding the real-time monitoring of load at the consumer end via DSL. ACKNOWLEDGMENT We are thankful to the XEN (Executive Engineer) Wazirabad, Subdivision Wazirabad, Gujranwala for providing their single feeder connected load data. PEER REVIEW INFORMATION Engineering Reports thanks Pengfei Liu and other anonymous reviewer(s) for their contribution to the peer review of this work. CONFLICT OF INTEREST The authors declare no potential conflict of interest. AU THOR CONTRIBUTIONS Muhammad Butt: Conceptualization; data curation; formal analysis; writing-review and editing. Saad Dilshad: Formal analysis; visualization; writing-original draft. Naeem Abas: Conceptualization; data curation; investigation; BUTT et al. 15 of 17 methodology; software; supervision. Shoaib Rauf: Investigation; methodology; resources; software; validation. Muhammad Saleem: Software; visualization. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. NOMENCLATURE AC alternating current CT current transformer DSL digital subscriber line DSLM demand-side load management DSM demand side management DTMF dual tone multi-frequency GDSM generic demand side management GEPCO Gujranwala Electric Power Company GSM global system for mobile communications IOT Internet of things kWh kilo Watt hour LCD liquid crystal display LNG liquefied natural gas RE renewable energy SLM smart load management system SMS short message system TOU time of use UPS uninterruptable power supply WAPDA water and power development authority Wi-Fi wireless fidelity ORCID Saad Dilshad https://orcid.org/- Naeem Abas https://orcid.org/- REFERENCES 1. Khan N, Dilshad S, Khalid R, Kalair AR, Abas N. Review of energy storage and transportation of energy. Energy Storage. 2019;1:1-49. https://doi.org/10.1002/est2.49. 2. 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